What is Android Privacy Sandbox?

The Android Privacy Sandbox is Google’s proposal for managing privacy-centric advertising, measurement, and attribution on mobile devices. 

This is a multi-year, open-source project aimed at pushing privacy standards forward while minimizing cross-app and cross-site tracking. The sandbox includes developer programs, design proposals, integration guides, API references, and more. 

Previously, Google introduced the Chrome Privacy Sandbox, which aimed to eliminate third-party cookies and minimize the use of Google Advertising ID (GAID). Android Privacy Sandbox officially marks the end of GAID, and thus the end of user-level insights on Android as well. GAID was critical for marketers, helping with attribution, personalization, remarketing, and third-party data sharing. 

What are the goals of the privacy sandbox?

In Google’s eyes, Apple’s “blunt approach” to privacy didn’t work: they believe forcing advertisers and developers to find an alternative on their own was not sustainable. Instead, Google’s strategy is to collaborate with them to provide an alternative path forward for everyone. 

Of course, this isn’t entirely altruistically motivated, as Google is financially incentivized to innovate their ad business, which accounts for 78% of their revenue.

Keep information private

From major data breaches to increasing distrust of social media platforms, consumers have become increasingly concerned about online privacy over the past few years. The trend was accelerated by Apple’s bold move: introducing the App Tracking Transparency framework, while simultaneously shifting their marketing messaging to “Privacy. That’s iPhone.” 

Google’s goal is similar – stay ahead of the curve and ensure they provide private solutions for their customers. 

Fund online publishers and developers

As discussed above, the goal is to share user data with third parties without compromising security and privacy. This now includes the removal of advertising ID. Google will need to preserve and build on their $238 billion ad business by slowly deprecating cookies and GAID, while providing new tech solutions to replace them.

Collaborate to set privacy standards

Google aims to collaborate with publishers, developers, advertisers, and even legislators, putting the company in a strong position to lead discussions on navigating privacy concerns. 

How does it work?

A good place to start with the sandbox is knowing that there are lots of parallels with Apple’s IDFA opt-in requirements. Google states that they’ll be phasing out the Google Advertising ID (GAID), while offering new tools to continue delivering personalized ads on free content. Here are the main components under the hood.

SDK runtime

Android uses app sandboxing, which helps the integration of third-party code via SDKs, while also setting guardrails for them. The SDKs are hosted within the sandbox, which also runs the potential risk of hosting (and, more importantly, sharing) undisclosed user data. SDK Runtime enables stronger guardrails, including a modified execution environment and limited permissions and data access rights for SDKs.

Attribution API 

Most mobile ad campaigns use Advertising ID to identify audiences across multiple channels and devices. The Attribution API registers attribution sources through certain triggers on an app or website. It then matches the triggers to the sources, and aggregates the data. 

The API has some limitations, including the limited number of bits available for event-level reports. There are also rate limits for available conversion triggers, and the number of ad techs per attribution source. 

Topics APIs

The Topics API aims to allow advertisers to serve ads based on a user’s interests, inferred from their app usage. The topic is observed by a caller, which is an app or third-party SDK within an app. The number of topics is limited to 469, to reduce the size of fingerprinting, and purposely excludes sensitive categories like religion, race, or sexual orientation.

Protected Audience (previously FLEDGE)

The Protected Audience API allows advertisers to create custom audiences based on app behavior, to enable remarketing and customer audience targeting without using private information. 

In simple terms:

How does Android Privacy Sandbox differ from Apple’s ATT?

While the goals of Apple’s ATT framework for iOS devices and Android Privacy Sandbox are the same, there are some major differences in execution.

The introduction of SKAdNetwork was disruptive. And to many, the Android Privacy Sandbox will be less so, because it provides a suite of tools to make the transition smoother for stakeholders.

Although Google is moving away from GAID, Google Referrer isn’t going anywhere (in the foreseeable future at least). This unique URL passes from the Play Store all the way to the conversion, giving advertisers insights into the user journey. iOS doesn’t have this capability at all. 

What are the potential challenges?

Changing times come with their own challenges. Here are a few you may encounter when working with the privacy sandbox.

Technical issues in adopting existing measurement strategies 

The first and biggest challenge is the technical implementation of the privacy sandbox itself. To get started, you need to complete the enrollment process, set up your development environment, configure permissions, and set up devices to use the Privacy Sandbox on Android. Since the program is still in beta, Google is slowly rolling out beta APIs which will have technical hiccups along the way (and won’t be available to everyone immediately). 

Limited data

Yes, the golden age (for advertisers) of unlimited user data is long gone. Anything in comparison to the wild wild west of mobile advertising will feel like a downgrade in terms of data access. As mentioned in a previous section, increased privacy measures mean limited datasets, forcing advertisers to think more creatively about how they want to target new audiences within Google’s guardrails. 

Data accuracy

The cost of privacy is weaker data signals. While we’ll be able to achieve granular and rich data, you’ll have to trade immediacy for accuracy. If you want quick reporting, there’s a higher chance the data will not be as conclusive, to protect the privacy of those few users. But reports with a longer callback will prove to be more accurate.

What are the future trends for Android and privacy?

Google highlights that this is a multi-year effort for a reason. Introducing massive changes to a multi-billion dollar industry requires time, and more importantly, lots of testing. Here are a few trends that we believe will take shape in the near future.

First-party data + AI

Collecting first-party data around in-app behavior is crucial for advertisers to offer tailored messaging and creatives. Today, AI tools supercharge first-party data by reaching new audiences similar to yours, predicting audience segments based on user-level behavior, and segment audiences based on behavioral patterns that may be missed by the human eye. This level of granularity will become increasingly difficult to achieve as we move to a privacy-first ecosystem. 

Deep linking and referrals

Deep linking will become more crucial for advertisers and developers to track in-app behavior while providing a seamless user experience. Deep links are links that direct the user to a specific page on a mobile site or app, without leaving the app altogether. This ensures users remain within your app’s ecosystem, and provides rich data that yields granular insights for your campaigns. 

How to prepare for Android Privacy Sandbox

While these changes may sound daunting, there’s a lot you can do to make the transition as smooth as possible. GAID isn’t going to disappear overnight, but taking proactive measures to maximize your campaigns in a privacy-centric world will save you a ton of headache down the road. Here are a few ways to get started.

Review your techstack

This change will impact your entire data ecosystem. Your MMP, CRM, and ad agencies will enter a trial by fire. There will undoubtedly be a learning curve to identify the most effective ways to advertise. Start by taking stock of your current techstack, and getting familiar with the new APIs within the sandbox.

Enroll and register for the beta program, and set up your devices

Enroll in the Privacy Sandbox program to get started. The developer enrollment program verifies each app that calls APIs, adding a protective layer in a controlled environment to minimize the misuse of data. Be sure to read the guidelines and understand that your enrollment will be made public.

Identify use cases and design them within the framework of Sandbox to test if they work

Since the privacy sandbox is still in its early stages without any clear timelines, a good place to start is by identifying your unique use cases. Then visit Google’s resource to see how other apps have solved them. 

Speak to your MMP about measurement solutions 

To prepare for the inevitable deprecation of GAID, your MMP should already be building solutions and testing the APIs to help solve for any data gaps — it’s definitely a top priority for us here at AppsFlyer. Working with your MMP ahead of time will help you make the transition gradual, avoiding a last-minute bombshell.

Key takeaways 

• The Android Privacy Sandbox is Google’s initiative to build a mobile ecosystem that preserves user privacy while allowing advertisers and developers to provide personalized experiences.
• The three main goals are to keep information private, fund online publishers and developers, and collaborate to set privacy standards.
• The simplified changes are as follows: targeting is becoming Topics, measurement is becoming Attribution API, and remarketing is becoming Protected Audiences API.
• Potential challenges in implementing the sandbox include technical implementation, limited data, and data accuracy.
• Android Privacy Sandbox is a multi-year project that will be shaped by trends like first-party data and AI, and increasing use of deep linking. 
• There will be a transition period, but it’s a good idea to get ahead now by reviewing your techstack, enrolling for the beta program, and getting your devices set up. You should also identify your own use cases and discuss the changes with your MMP. 

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The term “in-app” describes any activity or feature that takes place inside a mobile app, with the aim of enhancing user engagement and experience.

What is “in-app”?

The term “in-app” can be used to describe any activity, feature, or content accessed inside a mobile application – as opposed to those that take place on a web browser or elsewhere. 

In-app functionalities are designed to enhance user engagement, offer convenience, and provide a seamless experience where the user doesn’t have to leave the app environment. From advertising to purchases, events, notifications, and feedback, in-app features allow marketers to interact with users in a personalized and immersive setting. 

Common in-app activities

In-app advertising

In-app advertising refers to ads displayed within a mobile app. These can range from simple banner ads and interstitials to more sophisticated formats, like rewarded videos and native advertising. 

The key advantage of in-app advertising lies in the ability to personalize it: marketers can target users based on their interests, app usage patterns, preferences, and behavior. For instance, an ad for a fitness app might appear within a health and wellness app, directly reaching individuals who have shown an interest in keeping healthy. 

In-app advertising is a major revenue stream for app publishers, as advertisers pay them for the space based on the number of impressions or engagements their ad receives.

In-app purchases (IAP)

In-app purchases (IAPs) allow users to buy goods or services within an app. These purchases can be consumables (like in-game currency), non-consumables (like the option to remove ads), or subscriptions that unlock premium content or features. IAPs provide a direct revenue stream for both developers and marketers. At the same time, they can enhance the user experience by adding to or improving the app’s core functionality.

In-app events

In-app events are activities or milestones within an app, such as completing a level in a game, attending a virtual event, or achieving a personal best in a fitness app. These events help engage and retain users by providing a sense of progress and accomplishment. Marketers can use in-app events to trigger personalized communications or rewards, encouraging continued app usage and loyalty.

In-app notifications (In-app messaging)

In-app notifications are messages that appear while a user is actively using the app. They can be used to let users know about new features, promotions, or in-app events, helping to boost engagement and encourage the user to take specific actions within the app. 

Unlike push notifications, which can be sent any time, in-app messages only reach users when they’re engaged with the app, ensuring high visibility. 

In-app feedback

In-app feedback mechanisms allow users to provide comments or report issues directly within the app. This direct line of communication between users and developers or marketers is invaluable for improving app quality, user satisfaction, and engagement. Feedback can take the form of surveys, feedback forms, or interactive prompts that encourage users to share their experiences and suggestions.

Key takeaways

1. The term “in-app” describes any activity, feature, or content accessed within a mobile app, aimed at enhancing user engagement and offering a seamless experience.
2. In-app advertising targets users with ads based on their app usage and behavior, offering a high degree of personalization for marketers and a key revenue stream for app publishers.
3. In-app purchases enable users to buy goods or services directly within an app, providing a direct revenue stream and enhancing the user experience.
4. In-app events engage users by marking achievements or milestones, encouraging continued engagement and app loyalty.
5. In-app notifications deliver messages to users while they’re active within the app, ensuring high visibility and engagement.
6. In-app feedback allows users to communicate directly with app developers or marketers, providing valuable insights for app improvement and user satisfaction.

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What are App links?

App Links are custom URLs that direct users to a specific location. This might be an official app store listing (in which case the link is called an app store link), or a web page outside of the app that’s launched within the app itself (this is known as a deep link). 

Note that the term “App Link” is specific to Android devices — the iOS equivalent is Apple Universal Links. 

How do App Links work?

Once a user clicks on the App Link, they’ll be directed along one of two paths, depending on whether or not they have the corresponding app installed.

If the app is installed, the user will follow a deep link and launch the app, landing directly in the relevant app content.
If the corresponding app is not installed, a deferred deep link will direct the user to the app store page to download it, and then take them to the relevant in-app content once the app is installed and opened.

What are the other types of links? 

There are three types of App Links that operate in their own unique ways:

• Web links are standard links that direct users to a web page.
• Deep links direct users to a specific location within a mobile app. 
• Dynamic links send users to different locations depending on the user’s behavior. For example, if a user doesn’t have an app installed, they can be directed to the relevant app store. If they do have the app installed, they can be directed to a help article within the app.

What are the benefits of App Links?

App Links help users and app marketers alike. From increased security, to more accurate measurement, there are many reasons App Links are crucial for apps today.

Smooth user experience

App Links direct users to exactly where they need to be — whether that’s the app store or a specific location in-app. Deep links can also transition users between an app and web pages without having to close or switch between apps, making for a seamless user experience. 

Increase app conversions and retention

Better user experience leads to improved app conversions by reducing friction. Sending users to your intended in-app location helps tighten your conversion funnel without risking them getting lost in navigating to the next stage of the process.

Accurate attribution

Post-IDFA changes are already making it more difficult for mobile marketers to accurately measure their campaigns. Deep linking enables user acquisition managers to track and attribute app installs, conversions, and actions, because user behavior is all completed within the app, rather than another app browser.

Safer experience

Android requires app developers to verify corresponding apps with their web pages, improving security standards and creating safer app environments. 

How to set up App Links

The App Link itself needs to be generated by your developer. There are four key steps to this process, which are outlined in detail in our developer blog — here’s a quick summary:

1. Create a SHA256 fingerprint as a security measure to ensure you’re associating your app with the corresponding website. This prevents unauthorized handling of links and tampering.

2. Create intent filters to specify which URLs to map to your app. Android developers can use App Links Assistant from Android Studio to streamline the process.

3. Generate a Digital Assets Links file to link your website with your app. For a step-by-step guide, check out our setup instructions here.
   
4. Test your App Link before you begin sharing it. If you’re using App Links Assistant, simply click Test App Links. Otherwise, test the link on different channels to ensure it’s directing you to the intended location.

Key takeaways

• An App Link is a URL that sends mobile users to a specific app location, app store listing, or external website.
• There are three types of App Links, which each work in their own way: web links, deep links, and dynamic links.
• App Links improve user experiences, increase app conversions, provide more accurate attribution, and elevate safety measures. 
• Setting up App Links is a job for a developer, and involves a four-step process. 

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ROAS is short for return on ad spend. It is a metric that helps app marketers understand which campaigns and ads are working (and which aren’t) by measuring how much revenue was earned in comparison to how much budget was spent.

ROAS is typically expressed as a ratio and the higher the ratio, the better the campaign performed. 

So let’s say you invested $1,500 on ad spend for a campaign which resulted in $6,000 in revenue for your app – your ROAS would be 4:1 meaning for every dollar of ad spend, you made $4 in revenue. The calculation for this would look like the following:

Having a low or high return on ad spend is often a good indicator of overall campaign performance and profitability and helps with making decisions around campaign spend and media source diversification. 

That said, to fully understand performance, it’s necessary to take into account other metrics like CPA, LTV, and ARPU, among others… but we’ll discuss that more below.

In short, ROAS is kind of like ROI but specifically for campaigns driving traffic to mobile apps.

Why does ROAS matter?

ROAS is important because it helps answer the very basic (and essential) question “are my app marketing efforts actually working?” and guides decision making around where to invest more budget, and where to scale back. 

For example, if you ran a campaign that delivered top-quality users who generated significant revenue in your app, but you actually ended up paying more than you gained from those users, that campaign can’t be considered a success – and that’s exactly what ROAS helps you determine.

It’s good to look at ROAS on a few different levels, from the birds eye view of advertising budget and platform-specific campaigns down to a single campaign, ad set, ad, and even creative depending on what types of insights you are hoping to extract.  

Side note: Even a partial ROAS can be really valuable, especially if predictive analytics are involved. For example, let’s say you find that users who generate 50% or more of their cost by Day 3 are highly likely to become profitable users by Day 30. You can use this insight to cut off underperforming ad sets to ensure your ROAS stays positive. 

However, while ROAS is a powerful metric on its own, it doesn’t tell the full story and to truly understand performance, you need to look at metrics like CPA, ARPU, and LTV as well. 

All of these metrics combined will help you make better decisions on future budget, marketing strategy, and even your product roadmap.

Luckily, ROAS is easy to calculate — just use this formula:

The result is expressed as a percentage. For example, if you spend $1,000 on an ad campaign and you make $2,000 in profit, your ROAS would be 200% (100% is the break-even point — more on this later).

Of course, you could end up with a negative ROAS. For example, if you spent $100 on your ad and only generated $50 in revenues, your ROAS would be 50%. 

A negative ROAS means it’s time to reassess your creatives and marketing channels to discover where the problem lies, and optimize accordingly. 

What are the pros and cons of using ROAS?

ROAS is clearly a useful metric, but it’s not perfect. Let’s dig a bit deeper into the positives and negatives. 

Advantages of using ROAS

Staying on top of your ROAS can have big benefits for your marketing campaigns. Here are some of the ways it can help you:

• Choose the best channel. Most campaigns use multiple channels, such as email, social media, and out-of-home. By measuring ROAS across all of your channels, you can see which give you the most bang for your buck — allowing you to focus on those, and ditch any that are draining your budget for little reward. 
• Optimize your ads. By comparing ROAS across different ad creatives, you can identify which words and images resonate most with your audience. Then, give them more of what they like. 
• Make reporting easy. A lot of businesses like ROAS because of its simplicity: ads go out, money comes in. It’s a quick snapshot that’s simple to explain, even to non-marketers. 
• Take out the guesswork. Once you see what works and what doesn’t, you can use that insight to shape future marketing strategies and campaigns. Planning smarter will save you money and bring results faster. Plus, it’s easier to justify your ideas to management when you have the data to back them up.
  
  One caveat: just because something has worked in the past, doesn’t mean it always will! So, while ROAS is a useful guide to campaign performance, it’s not a case of one-and-done — you should always keep testing and measuring. 

Limitations of using ROAS

Of course, no metric by itself is a silver bullet — even one as powerful as ROAS has its drawbacks. Here are a few you should be aware of.

• It’s focused on the short term. Sure, you can set the timescale for which you want to measure ROAS, but it tends to be relatively short. That’s because you’re measuring behavior that can be directly linked to a specific ad. To understand your revenue over the longer term, you need to look at customer lifetime value (LTV). 
• You don’t see the bigger picture. Your ads don’t exist in a vacuum: it may be a Facebook ad that someone ultimately clicks on, but that might be because they’ve previously seen a poster, read a review, or been nudged by a friend. Or maybe they already know and like your brand. Advertising is just one part of the marketing mix, making it hard to prove that returns are entirely due to spending on one ad. 
• It doesn’t show volume. You can get a positive ROAS with a relatively small number of customers. Perhaps you just ran a very cheap campaign, so your revenue looks high in comparison. But how much higher could it be if you’d succeeded in attracting more customers?

Finally, it’s worth considering how privacy rules affect ROAS. Heightened privacy in the post-iOS14 era has certainly made it harder to get a handle on this metric: data has become more fragmented across networks, making attribution trickier, and accuracy isn’t guaranteed either. 

For a deeper dive into ROAS privacy issues and solutions, check out our blog on the challenges of measuring ROAS in a privacy-centric world.

Break-even ROAS

We’ve covered positive and negative ROAS, but there’s another term you should know. Break-even ROAS is the point at which you cover the costs of your advertising: it hasn’t made you a profit, but it hasn’t lost you money either. 

Break-even ROAS is a helpful benchmark to keep your ad spending on track, and in some cases it might be all you need to aim for. If you’re running an awareness campaign, for example, you wouldn’t expect ads to generate huge sales. But if you’re advertising to boost revenue, you may set a higher target. 

You can use the following formula to calculate your break-even ROAS, expressed as a percentage: 

(To calculate your average profit margin, take your average order value and subtract your average order costs. Then turn that into a percentage:

Average profit margin % = average profit margin / average order value x 100.) 

Let’s say your app costs on average $3 per customer to produce, and you sell it for $5 — you’re making an average profit of $2 on each sale. 

Your average profit margin is 2 / 5 x 100 = 40%. 

Then, your break-even ROAS is 1 / 40% = 250%. 

That’s the level at which your ad campaign pays for itself. 

ROAS vs other metrics

Do you know your ROAS from your ROI? With so many marketing metrics available, and a whole alphabet of acronyms being tossed around, it’s easy to get confused. Let’s cut through the jargon to find out how the terms differ, and how they work together.

ROAS vs ROI

Both ROAS and ROI (return on investment) help you  understand if your campaign was successful or not, but that’s where the similarities end. 

ROI first calculates the total cost of the advertising campaign. That includes not just the cost of the ad itself, but any other resources involved such as IT, software costs, design, and distribution. It then looks at the profit and assesses the overall return on investment for the campaign.

The difference is that ROAS focuses purely on the profit generated from direct spend on an ad campaign. It doesn’t factor in the additional costs, only the cost of placing the ad and how much money you generated as a direct result. 

Whereas ROI is used broadly across businesses and functions, ROAS is a pure marketing term and the foundation for understanding your campaign’s success.

Learn more about the difference between ROI and ROAS. 

ROAS vs CAC

Your customer acquisition cost (CAC) shows what it costs you to acquire a new paying customer. You calculate it by dividing your total campaign spend by your number of paying customers. 

For example, if you spent $2000 on a campaign and gained 200 customers, your CAC would be $10 per customer.  

CAC and ROAS both measure the results of your spending, but CAC is based on the number of customers you’ve acquired — whether they turn out to be valuable or not. With ROAS, you can see how much revenue those customers have brought you.   

Looking at ROAS can help you make sure you’re acquiring valuable customers, and focus your efforts in the right places. 

ROAS vs. eCPA

eCPA is the effective cost per action, and measures the actual results of a campaign from a cost perspective. For example, if you spend $1,000 on an ad campaign and receive 200 actions (such as clicks), your eCPA is $5. 

While ROAS and eCPA both provide a monetary evaluation of a campaign’s success, total generated revenue is not factored into the ‘actions’, only the number of occurrences. 

If the ‘action’ was defined as an in-app purchase, and you know these 200 actions generated $1,500 in revenue, you could find the ROAS by dividing 1,500 by 1,000 (150%). 

eCPA should be up there with ROAS on your list of key campaign metrics. If your ROAS is underperforming and your eCPA is below target (meaning you’re paying more than you intended to pay for an action), you need to optimize as quickly as possible to get your campaign back on track. 

ROAS vs. CTR 

CTR stands for click through rate and is calculated by dividing the number of clicks by the number of impressions served. 

Since a high CTR is a good indicator that your ad resonated with the audience, it’s sometimes used as a measure of how successful a creative was in driving action (a click). 

CTR differs from ROAS because it only provides indications of a campaign’s creative — not the overall campaign performance.

What’s a good ROAS?

This is an age-old question asked by marketers the world over. The honest answer is that there is no answer. 

The main thing to remember is that good  ROAS is positive ROAS. And it could take time, sometimes months, to drive a profit from a user or campaign. 

But what is a good ROAS for one organization might be worrying for another, depending on their targets.  

For example, profit margins in a hyper casual gaming app are very low, since ad revenue is often just a few cents per view. This means CPI (cost per install) is cheaper and scale is the name of the game to drive profitability. 

A subscription-based app like Netflix or Spotify, on the other hand, can generate higher margins thanks to recurring subscription revenue, despite relatively high acquisition costs. 

Good ROAS also varies according to your advertising platform. For example, research from Databox shows that companies typically achieve a return of 6x to 10x (in other words, 600% to 1000%) on Facebook ads. For Google Ads, on the other hand, average ROAS is around 200%. 

These numbers might sound impressive, but remember, they’re just averages. They’re not broken down by industry, company size, or audience, so don’t panic if your own results look different! 

What is a target ROAS? 

Target ROAS is a bidding strategy whose aim is to hit a specified (user) value. That means you set a target order value for each dollar you spend on your campaign. 

Unlike with other Adword bidding campaigns, where Google controls the bid through algorithms and automated processes, target ROAS requires its own bid strategy as there is no standard version. 

For some verticals, targeted ROAS can be a useful tool: for example eCommerce, where the goal is to drive in-app purchases. However, be aware that targeted ROAS requires a minimum number of conversions (Google recommends at least 15 conversions in the last 30 days in the same campaign). Without these it will be difficult for Google to hit the desired target. 

Nine ways to improve your ROAS 

A marketer’s goal is always to increase revenue and conversions. So let’s look at a few ways you can improve your ROAS. 

1. Set benchmarks

To know what your target should be, you first need to understand what qualifies as good ROAS and set that as a benchmark. Knowing the baseline for each campaign and channel can help highlight where you’ve been successful, and serve as a model for future campaigns. 

2. Test and learn 

Achieving a good ROAS will be dependent on a number of factors, so it’s important to test which campaigns, creatives, and channels deliver the best results and most valuable users. Use A/B testing to experiment with different creatives, placements and targeting strategies.  

3. Optimize your landing pages

If your ads are getting plenty of clicks, but your ROAS remains stubbornly low, look closely at where the ads are taking people. Is your landing page clear and engaging? Is the look and feel aligned with the ad? Does the page load quickly? Are calls to action clear? 

There are lots of tweaks you can make to keep users moving smoothly through the purchasing journey.  

4. Lower the cost of your ad

It may seem obvious, but one way to get more return on your spend is to reduce that spend. You can do this by improving your quality score. A better quality score results in higher ranking ads and therefore a lower cost per click (CPC). 

Keywords impact cost too. Rather than going for the most popular terms, look for long-tail keywords or those more targeted to your niche. 

You can also introduce negative keywords, which help exclude users who may be looking for a similar item to what you’re advertising but not that exact item. 

For example, your shopping app has a winter deal for scarves. You can exclude users who are searching for winter gloves, as they’re likely to ignore your ad and diminish your CTR. Worse, they might click on your ad, realize it’s not relevant to them and move on, costing you money for the click and giving you nothing in return. 

5. Know your audience

Carry out robust customer research to understand where your ideal customers are, when they’re online, and what they’re interested in. If you know they’re parents who follow food content on Facebook, for example, there’s a good chance they’ll be interested in your family recipe app. 

By carefully aligning your message to your audience, you’ll drive higher conversions and stop wasting money on the wrong channels.

User acquisition (UA) toolkit for 2023

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6. Re-engage high value users to increase revenue

Re-engagement is much cheaper than UA, and can even be free if you use your owned channels. If you have a cohort of users who have delivered a high ROAS then it’s important to re-engage and encourage them to repurchase. 

One way to do this is through a limited time offer. That way they feel as though they’re getting a good deal as well as being appreciated and valued users. 

7. Bid smarter

Experiment with different bidding strategies to find the most cost-effective approach. You may find you save money by adjusting your maximum bid, using automated bidding, or setting different bids for desktop and mobile. 

8. Use predictive analytics

Knowing how your most valuable users monetize throughout their lifetime using your app can be a game changer with ROAS optimization. If you can correlate early actions in the funnel with future monetization, you can significantly improve your ROAS. 

For example, if you find that users who complete level 10 of your game within the first 24 hours of play are highly likely to make in-app purchases, you can use this data to optimize the campaign after 24 hours, instead of waiting for more signals later in the funnel. That way, you can cut waste and meet your revenue targets. 

9. See the bigger picture

If customers are dropping out on their way to the checkout, investigate why. Is your price too high? Are you asking for too much information? Is the process confusing? Look beyond advertising to see how you can optimize the entire customer journey.

Frequently Asked Questions

Key takeaways

• ROAS is among the most important metrics for marketers. High-value users don’t mean much if you paid more to acquire them than the amount they spent in-app. 
• But ROAS can’t tell you everything – use it alongside other metrics including ROI, CAC, CTR and eCPA. 
• Good ROAS is dependent on your company and the platform you’re using, but it should be positive. Remember that achieving positive ROAS in a campaign can take months.
• Break-even ROAS is a useful benchmark to ensure you cover the costs of your advertising activity. 
• Early indications of revenue will allow you to measure your partial ROAS to help you understand if you’re heading in the right direction, and how you could optimize your campaign.
• To improve your ROAS, you need engaging content and a seamless customer journey. Also, consider ways to cut advertising costs, for example by refining your bidding and keyword strategies.

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What is a second price auction?

Second price auction is a type of auction model used in programmatic advertising. As advertisers bid for ad impressions, the highest bidder wins — but there’s a catch: instead of paying their own bid amount, the winner pays the second-highest bid amount plus one US cent. 

Consider this example involving three different advertisers:

• Advertiser A bids $2
• Advertiser B bids $1
• Advertiser C bids $2.12

Though Advertiser C is the highest bidder and wins the auction, they don’t pay their initial bid of $2.12. Instead, they pay $2.01 for the ad impression — the second-highest bid ($2 from Advertiser A) + $0.01.

When talking about second price options, it’s important to mention the bid floor.

While not mandatory, a bid floor sets a minimum amount that auction participants must meet or exceed when placing their bids. As well as ensuring better deals for publishers, this ensures transparency and integrity in the auction process, creating an environment where participants are motivated to submit bids that genuinely reflect the value they place on advertising.

How is it different from first price auction?

In a first price auction, the highest bidder wins, and they pay the exact amount they bid for the item or service. It’s a straightforward model where the winning bidder’s proposed price determines the transaction cost. 

Here’s a brief breakdown:

• Bid winner: The participant with the highest bid is declared the winner.
• Payment: The winner pays the amount they bid, so there’s a direct correlation between the bid amount and the final price.

So, in our previous example, Advertiser C will win the auction again, but this time, they’ll be paying $2.12.

In contrast, a second price auction introduces a unique pricing mechanism. The highest bidder still wins, but they don’t pay their proposed amount. The specifics look something like this:

• Bid winner: The participant with the highest bid is still the winner.
• Payment: Instead of paying their bid amount, the winner pays the amount of the second-highest bid, plus $0.01.

Which is better: First price or second price?

Each auction model has its pros and cons — let’s compare them. 

First price auction:

• Advantages: Simple and intuitive; participants pay what they’re willing to bid.
• Disadvantages: Bidders might strategically submit lower bids than their true valuation, leading to inefficient pricing; the winner might pay more than the actual value they placed on the item.

Second price auction:

• Advantages: Encourages fair bidding; participants have less incentive to manipulate their bid. Efficient pricing. 
• Disadvantages: Bidders may find it difficult to strategize due to the indirect relationship between their bid and payment.

Deciding between first price and second price auctions depends on a few things like

transparency, bidder behavior, and how much complexity you’re willing to deal with. If you prefer to keep things simple, go for the first price auction. But if you want a fair and honest bidding process, then the second price auction is the way to go.

In both cases, setting a bid floor is optional but helpful for preventing unrealistically low (or high) bids.

What are the benefits of using second price auction over first price?

Choosing a second price auction over a first price auction yields multiple advantages, such as: 

Fair, truthful bidding

The emphasis on truthful bidding in a second price auction encourages participants to bid their actual value, fostering honesty in the auction process. This contrasts with first price auctions, where bidders might strategically undervalue themselves. 

Reduces overvaluation risks

Ever heard about the winner’s curse? It refers to a situation where the winning bidder in a first price auction might end up overpaying if their bid significantly exceeds the actual value of the item. In a second price auction, the winner avoids this issue by paying the lower, second-highest bid.

Simplicity in valuation

Bidders in second price auctions don’t need to precisely estimate an item’s value to avoid overpaying; they simply bid their true value, streamlining the bidding process.

Transparency in the market

The predictability of the second price auction allows advertisers to better understand market dynamics. This insight helps them make informed decisions, avoiding inflated perspectives and enabling more competitive, data-driven practices.

Predictable costs

Predictable costs in a second price auction help bidders with budget planning. Knowing they’ll pay the second-highest bid plus a small increment provides a clear and predictable cost structure, enhancing financial planning and management.

Encourages participation

In a second price auction, participants feel more at ease and motivated to engage, knowing the outcome is determined by the second-highest bid rather than their own bid. This fosters a more dynamic and inclusive auction environment. 

Bid strategies for second price auctions

Now to the fun bit! 

Let’s delve into key bid strategies you can apply for second price auctions:

1 — True value bidding

Strategy: Participants in a second price auction are encouraged to bid their true value for an item or impression. This means placing a bid that accurately reflects the maximum amount they’re willing to pay. For instance, if you believe an impression is worth $2 to you, bid exactly $2 for an honest reflection of the impression’s value.

Why it works: Bidders can be confident they’ll pay only the second-highest bid amount, promoting honesty and transparency. This approach helps you avoid overpaying while remaining competitive. 

2 — Bid shading

Strategy: Bid shading involves adjusting bids to a level just above the expected second-highest bid. Here’s how it works: Suppose the estimated second-highest bid is $1.50. Following the bid shading approach, consider placing a bid at $1.51 to secure the auction while paying a price just above the second-highest bid (hence winning the auction).

Why it works: By shading the bid slightly below the bidder’s true value, you can balance competitiveness and cost-effectiveness. This tactic helps secure the win while paying a lower price.

3 — Dynamic bidding

Strategy: Adapt your bids dynamically based on real-time auction conditions, competitor behavior, and performance data. For example, if a sudden influx of competing bids occurs, adjust your bid upward to stay competitive and increase your chances of winning.

Why it works: Bidders continually analyze the auction landscape, adjusting bids based on factors like the number of competing bidders, historical bid patterns, and the value of the impression. This approach ensures your bids remain relevant and competitive.

4 — Bid experimentation

Strategy: Conduct bid experiments by testing different bid amounts to assess their impact on winning auctions and achieving campaign objectives. For example, make bids of $1.50, $2.00, and $2.50 to analyze which bid level consistently results in winning auctions while achieving campaign objectives.

Why it works: Bid experiments are great for understanding the optimal bid level for your goals. This data-driven approach helps you refine bidding strategies over time.

5 — Budget allocation

Strategy: Allocate your budget strategically across multiple auctions to maximize overall campaign performance. If certain auctions consistently yield better results, allocate more of your budget to those auctions to maximize returns.

Why it works: Instead of focusing solely on individual bids, consider your broader campaign budget. This involves allocating funds to auctions with higher potential returns while staying within your overall budget constraints.

6 — Competitor analysis

Strategy: Monitor and analyze competitors’ bidding behavior to gain insights into their strategies. For example, if a competitor consistently wins auctions with higher bids during peak hours, adjust your bidding strategy to remain competitive.

Why it works: Observing and understanding how competitors bid in the auction enables you to adjust your bidding strategies accordingly, ensuring a more informed and competitive approach.

7 — Auction segmentation

Strategy: Segment your bids based on different factors such as audience segments, time of day, or device types. For instance, bid higher for impressions targeted at a premium audience segment. Similarly, adjust bids based on the historical performance of certain devices.

Why it works: By tailoring bids to specific segments, you can optimize your bidding strategy for different audience behaviors and preferences, improving the efficiency of bid allocation.

8 — Bid floor optimization

Strategy: Experiment with bid floors to find the optimal minimum bid that balances competitiveness and efficiency. For example, test bid floors at $1.00, $1.25, and $1.50 to identify the minimum bid that ensures competitiveness without overpaying for impressions.

Why it works: Bid floors set the minimum acceptable bid, and optimizing this value helps strike a balance between winning auctions and controlling costs.

9 — Bid adjustments

Strategy: In your bid strategy, you make bid adjustments based on factors like audience targeting, device types, or geographic locations. Consider increasing bids for impressions from a high-value audience segment, or adjusting bids higher during peak hours to enhance visibility and competitiveness.

Why it works: By adjusting bids for specific conditions or segments, you can optimize your strategy to maximize the chances of winning auctions in scenarios where certain factors influence the value of impressions differently.

Key takeaways

• In a second price auction, the winning bidder pays a price just above the second-highest bid, creating a distinctive pricing mechanism where the highest bid doesn’t determine the final cost. 
• While not obligatory, a bid floor, setting a minimum amount participants must meet, ensures transparency and integrity in the auction. This approach encourages participants to submit truthful bids.
• The main difference between first price auction and second price auction lies in how winners determine their payment. In a first price auction, the highest bidder pays exactly their proposed amount. 
• The first price auction is straightforward but can result in inefficient pricing due to strategic bidding. In contrast, the second price auction promotes fair and honest bidding, lowering the risk of overvaluation. However, it can be challenging to strategize due to the indirect link between bid and payment.
• Second price auction offers several advantages, including promoting fair and truthful bidding. It mitigates the risk of overvaluation, simplifies the valuation process, provides predictable costs for budget planning, and encourages broad participation in the auctions.
• As a bidder, you can deploy various bid strategies to navigate second price auctions effectively. These strategies include bid shading, bid adjustments, dynamic bidding, and competitor analysis.

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What are in-stream ads? 

In-stream ads are short, snappy advertisements placed within popular social media video content. They’re timed as pre-roll, mid-roll, or post-roll (we’ll explain these terms in just a minute), ensuring your message hits users when they’re most engrossed in the content for maximum impact. 

In-stream ads go beyond just YouTube videos, seamlessly blending into content like Facebook livestreams and Instagram Stories to grab your attention as you scroll. 

Note that these ads are intentionally non-skippable for a brief period — usually 5-30 seconds. That might sound short, but with your audience so focused and primed to engage, it’s a real opportunity to make your mark.  

Types of in-stream ads

In-stream ads can be broken into the following three categories:

1 — Linear ads

The most common form of in-stream ads, linear ads disrupt the main video content. Taking up the entire video playing space, they’re called “linear” because they play sequentially with the content — similar to commercial breaks on traditional TV, which come between and during shows. 

Here are three types of linear video ads:

• Pre-roll: Before your video content kicks in, pre-roll ads make their entrance, lasting for 15, 30, or 60 seconds. They offer a tried-and-true method for brands to boost awareness, recollection, and purchase consideration. While users might have the option to skip these ads, the key is to craft engaging content in the initial moments to ensure a positive and lasting impression.

• Mid-roll: Shown right in the middle of your video content, mid-roll video ads are the shorter versions of pre-roll ads. Capitalizing on the fact that users have already invested time in watching the video, mid-roll ads have lower abandonment rates and higher completion rates. This makes them a good option for brands aiming to ensure their entire ad gets the spotlight – if only for a few seconds.

• Post-roll: Post-roll ads play as the grand finale at the end of your video content. Despite being the least used in-stream format, these can be remarkably effective. Users, having watched their intended video, are more likely to take the next step and click through to a page. 

2 – Non-linear ads

Non-linear video ads, also known as overlay ads, appear on top of playing content without obstructing or interrupting it. This means they’re less intrusive than linear ads, allowing viewers to continue watching content while the ad is active. 

These non-linear ads can manifest as follows:

• Overlay banner: This non-linear ad format appears discreetly at the top or bottom of the screen during video playback. It adds a touch of promotion without disrupting the primary content, providing a subtle yet effective advertising tool.

• Overlay text: A non-intrusive companion to video content, overlay text appears during video playback, sharing valuable insights or information without interrupting the main narrative. This format enhances the viewer’s understanding without detracting from the core message.

• Branded canvas unit: The branded canvas unit transforms the screen into a captivating visual canvas. It takes the form of an L-shaped banner that briefly shrinks the video being played, allowing you to showcase your brand in an artistic and memorable manner. This simulates the ad experience from over-the-top (OTT) and connected TV (CTV) spaces on the web.

3 – Companion ads

Companion ads deviate from the strict definition of in-stream as they don’t appear directly within the video stream. Instead, they appear beside the video in the form of an image, text, or rich media ad, positioned outside the video player.

Despite their placement, companion ads play a crucial role in improving brand visibility and combating banner blindness. They’re often used along with linear or non-linear in-stream ads, hence the name “companion ads.”

In-stream ads vs. out-stream ads

We’re focusing on in-stream ads here, but there’s another, similar term you may have heard: out-stream ads. These play in non-video mobile content, for example when you’re scrolling through a newspaper article.
Here’s a table highlighting the main differences between in-stream ads and out-stream ads:

How to choose between in-stream and out-stream ads

The key differences between in-stream and out-stream ads boil down to where they pop up and how they blend into the user’s experience. 

In-stream ads cozy up within video content, creating a bit more interruption, while out-stream ads showcase their flexibility in various formats, offering a smoother user journey. 

When it comes to engagement, in-stream ads take the lead, capturing attention within playback content. However, out-stream ads, though (slightly) less engaging, provide more control to advertisers over where their content appears. 

Final verdict: Choosing between the two advertising formats depends on your advertising goals and who you’re trying to reach.

Benefits of using in-stream ads

Next, let’s review why you should include in-stream ads as part of your digital marketing campaign:

• Readiness: In-stream ads capitalize on the fact that viewers are actively seeking video content. Whether they’ve just clicked on a video, are in the middle of one, or have just finished watching, viewers are already in a video-watching mindset. This makes it more likely they’re sitting comfortably, with audio on, ready to engage with your content.

• High compatibility with OTT and CTV advertising: In-stream ads work well with services like OTT and CTV. This means that when people are enjoying shows or movies on these platforms, they can also see your ads. Not only can you achieve a wide reach this way, but you can use demographic, behavioral, or geographic data to get your ads in front of the most relevant audience segments for your brand. 

• Motivation: Viewers of in-stream ads, particularly non-skippable pre-rolls and mid-rolls, have a motivation to continue watching: to return to the original content. This creates a level of engagement and motivation to see the ad through. Also, the option to skip the ad after a brief period offers a balance, so you don’t alienate viewers who want the freedom to click away. 

• Attention: By momentarily interrupting their browsing routine, in-stream ads compel viewers to pay attention — even if it’s just for a few seconds — helping you break through the online noise and capture the audience’s focus. Unsurprisingly, the average social media ad click-through rate worldwide is 1.2%.

• Affordability: If you’re working with a tight budget, in-stream ads are a smart choice. Depending on the chosen keywords, the cost of views can be low, making it a cost-effective option for businesses with limited money. Plus, if you’re working on a cost-per-completed-view basis, you won’t waste your budget on viewers who don’t watch to the end. 

• Customization: In-stream ads offer marketers great customization flexibility. You get to decide if you want to make people watch the whole ad or let them click away after a certain time, like five seconds or one minute. So, you can customize your ad strategy to fit exactly what you’re trying to achieve with your campaign.

Challenges of in-stream ads

Despite the undeniable advantages, in-stream ads aren’t a perfect paid social advertising solution. Here are some of their biggest drawbacks:

• Intrusive user experience: In-stream ads, while disruptive enough to capture attention, can sometimes be perceived as intrusive. Consider it a flip side of their disruptive nature: viewers may find the interruption jarring, leading to potential negative reactions and unfavorable brand perception.

• Ad-compatible video player requirement: In-stream ads have a technical dependency: an ad-compatible video player for seamless integration. As a result, you have to ensure your chosen platforms and publishers support the necessary infrastructure for delivering the ad.

• Restricted availability: Some platforms may not support in-stream ad formats, restricting the diversity of channels available for advertisers to reach their target audience. This restriction may limit the impact of the ad, affecting the success of your advertising strategy.

• High cost per mille (CPM): Compared to other advertising formats, in-stream ads often come with a higher CPM, with advertisers paying a significant amount for every thousand impressions. This can strain advertising budgets, making it challenging for smaller businesses or those with limited resources to leverage this format effectively.

• Difficulty in aligning ads with playback content: A critical aspect of in-stream advertising is aligning the ad with the theme or tone of the video content. It’s a pivotal factor in sustaining viewer interest. To get this right, you need to plan carefully and understand both the target audience and the broader content landscape.

Best practices for in-stream ads

Creating and executing an effective in-stream ad campaign requires a nuanced approach. To set you on the right path, consider the following in-stream advertising best practices:

1 — Make engaging ads with swift impact

Consumers often click the “Skip” button within seconds. This means that time is of the essence and you need to get your message across before the viewer has the option to skip. 

How do you do that? Create ads that swiftly convey your message. Opt for action-packed scenes or concise product explanations, steering clear of unnecessary jargon. Be sure to highlight the benefits you offer, even if the allotted video time is limited to 30 or 60 seconds.

2 — Ensure it’s viewer-centric

In the brief span you have, focus your in-stream ad on the viewer. 

Address them directly to create a personalized experience — use the word “YOU” as frequently as possible. You can also use the phrase “so you can” as a powerful psychological language pattern, to keep the video benefit-focused and tailored for the viewer. 

For instance, structure your message around addressing a viewer’s pain point, showcasing how they can achieve a desired outcome. This personalized strategy resonates well, especially since viewers are actively seeking answers during their brief engagement with the ad.

3 — Differentiate with visual and auditory cues

Leverage visual and auditory strategies to make your ads memorable. Start by promptly displaying your brand logo and maintaining a consistent visual identity with colors and large fonts. 

If your target audience is already familiar with your brand, consider using established script structures for added resonance. For example, if your brand typically uses a humorous tone or storytelling style in your ads, continuing this approach will resonate with viewers already familiar with your advertising style.

Grab attention by incorporating vibrant colors, catchy music or phrases, and engaging movement — this trifecta will hold the viewer’s attention and keep them interested, ensuring your ad makes an impact. 

4 — Use simple and actionable CTAs

Use clear CTA (call to action) messages in the primary text, URL, and video content to encourage action. Avoid using vague language — instead of saying something like “Click here to find out more,” guide the viewer on what will happen and the steps to take. Even a straightforward ‘Shop Now’ works when placed in context:

5 — Add captions for greater accessibility

Subtitles and captions are crucial for viewers who watch without sound or have hearing impairments. Make sure to upload your video subtitles as .srt files for accuracy and to avoid transcription mistakes. This ensures a seamless viewing experience that’s accessible to a broader audience.

6 — Foster a sense of intimacy

Use camera tricks in your in-stream ads to build an emotional connection with your audience. For instance, you can crop in when featuring characters to fill the screen and engage viewers. Maintaining eye contact throughout the video is another excellent tactic to create a personal conversation feel, rather than a commercial presentation.

Key takeaways

• In-stream ads help cut through the online noise and prompt action. They seamlessly integrate with content, playing before, during, or after streaming videos. 
• In-stream ads come in two main formats: linear and non-linear. Linear ads disrupt main video content and include pre-roll, mid-roll, and post-roll ads. Non-linear ads, also known as overlay ads, appear without interrupting the content and include overlay banners, overlay text, and branded canvas units.
• Contrast in-stream ads with out-stream ads, which appear in non-video content. These give advertisers more control over placement, but because they’re less disruptive they tend to achieve lower engagement than in-stream formats. 
• In-stream ads capitalize on viewer readiness and motivation, providing high compatibility with OTT and CTV advertising. They’re attention-grabbing, cost-effective, and offer customization flexibility for marketers with tight budgets.
• Despite benefits, in-stream ads can be intrusive for viewers, prompting them to skip whenever they can. Other challenges include the need for special video players, higher costs, platform restrictions, and difficulties aligning ads  with content. 
• In-stream ads work best when you grab attention fast: use distinctive visuals and sounds, and get your message across as early as possible. Focus on the viewer by talking to them directly and addressing their pain points, and remember to include a clear CTA and accessibility features. 

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Hybrid video on demand (HVOD) is a revenue model for video streaming platforms that combines two or more income streams, like subscriptions (SVOD), advertising (AVOD), and transactions (TVOD).

And in the blink of an eye, the era of low-cost streaming is over. Having access to every Marvel, Pixar, Disney, and Star Wars movie for the price of a single movie ticket now sounds like a fantasy. Because while the race for subscribers initially drove prices down, streaming platforms have realized they can’t keep running on empty. 

Is video on demand in demand?

Streaming accounts for 38.1% of total TV usage in 2023, surpassing broadcast and cable. The result? The birth of a $159.90 billion industry.

The extremely competitive prices that came out of the ‘streaming wars’ made subscribing a no-brainer. Today, retaining subscribers while remaining profitable is the challenge streaming services need to tackle if they want to grow sustainably.

Striking that balance means offering high-quality and unique shows at a price point that subscribers can justify. 

But finding that perfect price point is no easy task. Recently, we’ve seen streaming services raise prices and crack down on account sharing. But, as the economic downturn takes its toll, that’s led to consumers canceling their traditional subscription video on demand (SVOD) subscriptions, turning to free, ad-supported services instead. 

The solution, it seems, is a hybrid pricing model, where platforms offer varying pricing packages with different features and ad frequency.

What is HVOD?

Hybrid video on demand, or HVOD for short, is a monetization model used by over-the-top (OTT) streaming platforms that combines two or more monetization strategies, including ad-supported tiers.

Like hybrid cars, which allow drivers to choose between electricity and gas, hybrid video on demand allows price-sensitive consumers to watch the content they enjoy at the price points that work for them. 

What are the benefits of HVOD? 

A hybrid monetization model allows streaming services to deliver a user experience that works for everyone. That means they can reach a wider audience, and no one has to miss out on their favorite shows. 

Here are a few more ways that HVOD benefits advertisers, publishers (the platforms themselves), and users.

Responding to consumer trends

Hybrid monetization models allow OTT platforms to flexibly package features and pricing to suit the economic climate and align with consumer trends. After all, an ad-free subscription service with a premium price tag may be the first “luxury” to go when budgets are tight. 

By having a range of price points, streaming services can also provide value in other ways, including 4K resolution, exclusive pre-releases, and gaming content.

Personalized ads

Advertising can be a lucrative alternative to subscription content – just look at YouTube. And the more relevant and personalized the ads, the better the response will be.
Increasingly, streaming services are offering a blend of ad-supported and ad-free subscription tiers, with the likes of Hulu, Netflix, Disney+, and Apple TV+ all jumping on the bandwagon. This approach means the platforms have the data they need to deliver highly personalized messaging through programmatic advertising. That translates into more engaged users, and more revenue for advertisers and publishers.

Lower churn and higher retention rates

The hybrid approach means that, when the streaming service inevitably raises its prices, it won’t alienate the entire customer base. Providing a lower-cost alternative helps retain a loyal user base while minimizing churn. 

How does HVOD differ from other OTT monetization models?

There are lots of acronyms to keep up with in the world of OTT, especially when it comes to monetization models. Since HVOD is a combination of two or more of them, here’s a quick refresher on what each one offers.

Subscription video on demand (SVOD)

With SVOD, subscribers pay a regular subscription fee to access the entire library of video content. This is the simplest revenue model, as it relies on predictable subscription growth rather than ad revenue.

Advertising-based video on demand (AVOD)

AVOD lets viewers access the content library for free in exchange for watching ads – the model you’ll recognize from YouTube. This is by far the most accessible revenue model with the largest audiences. 

Transactional video on demand (TVOD)

TVOD asks viewers to pay a one-time fee to watch an individual piece of content, like a newly released movie or a pay-per-view sports event. Typically, you can buy the content for unlimited viewing, or rent it for a limited time period or set number of views. 

Free ad-supported television (FAST)

FAST is the digitized version of cable television, where viewers can watch pre-programmed content for free, powered by advertising. Examples include Pluto TV and Peacock. 

Premium video on demand (PVOD)

With PVOD, viewers can pay for a pre-release or an exclusive piece of content for a fee on top of their existing subscription fee.

Broadcaster video on demand (BVOD)

BVOD is an on-demand streaming service that is tied to a traditional broadcaster, where viewers can watch their television programming online. BBC iPlayer is a well-known example. 

Virtual multichannel video programming distributor (vMVPD)

Similar to bundled sports packages offered by traditional cable companies, vMVPD offers subscribers a group of bundled digital channels for a flat fee that would typically be less than paying for each channel individually. 

How to generate more revenue with HVOD

As well as improving engagement and retention, HVOD gives you multiple revenue sources. Here’s how to get the most out of them. 

Upsell and cross-sell

Offering viewers a low barrier to entry opens up opportunities for OTT services to upsell and cross-sell their features and services. Free trials or free ad-supported tiers let potential subscribers watch shows that they’re interested in for free, before committing to a fully ad-free, binge-worthy experience.

Diversify your revenue sources

With HVOD, OTT services can test and experiment more freely than SVOD services, where customers may be hyper-sensitive to the flat fee. Enabling programmatic advertising allows more brands to connect with your premium audiences, contributing to increased and scalable revenue. On top of this, HVOD also opens the door to strategic content partnerships and affiliate advertising as alternative revenue streams. 

Make data-driven decisions

HVOD enables platforms to gather extensive user behavior data, both with and without ads. Most importantly, this data can highlight price sensitivity. 

This means OTT services can pinpoint features and content that drive the most value, allowing them to confidently adjust pricing or package up attractive bundles. Just don’t overdo it, as too many price changes could turn viewers off. 

Key takeaways 

• Hybrid video on demand (HVOD) is a revenue model for OTT subscription services that combines two or more income streams, like subscriptions (SVOD), advertising (AVOD), and transactions (TVOD).
• In today’s competitive streaming market, more platforms are adopting a hybrid model to broaden their audience and retain users. 
• Offering a range of price points also enables streamers to respond to consumer trends and personalize ads using programmatic technology. 
• HVOD opens up multiple revenue streams, as well as opportunities for cross-selling and upselling. It also provides OTT platforms with valuable behavioral data to shape and scale their offering profitably.

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AOV is the average value of all customer orders over a specified period of time.

What is AOV?

AOV, or average order value, is a metric used in eCommerce to measure the average amount customers spend per order over a certain period of time.

For instance, if you run an eCommerce business, you might analyze your AOV monthly to understand the typical order size. If you sell bars of soap online for $10, and you sell an average of three in each order for October, your AOV for that month would be $30. 

AOV is a dynamic number that fluctuates over time. Tracking it helps you analyze customer buying patterns and ROI on advertising spend, so you can take steps to improve your profitability.

How to calculate AOV

AOV is a simple calculation you can run in your eCommerce platform reporting or in a spreadsheet. First, create parameters or run a report for the period of time you want to analyze. Then run this simple formula:

To calculate your total order values, leave out sales tax but include the amount customers paid for products, shipping, and fees. For example, if your orders for Cyber Monday totalled $12,600 and you received 120 orders, your AOV would be $105. 

Why is AOV important?

First and foremost, AOV tells you how much revenue you typically receive with each order. By monitoring this, you can track and project your revenue over time and optimize your buyer journey for better profits. 

Here are the top benefits of tracking AOV:

1. Grow your revenue

Your AOV tells you how much your customers are ordering. A higher AOV generally points to greater success and revenue gain, since it means your orders were larger, higher value, or more frequent. 

2. Improve LTV

When you know your AOV, you can also improve your lifetime value (LTV), which is the average revenue per customer over their lifetime of buying from your brand. Once you understand which factors lead to larger orders (for instance, a customer loyalty reward or free shipping above a certain spend), you can deploy those tactics to encourage repeat purchases and larger orders.

3. Improve margins

Since gaining a new customer is hard work and expensive, a higher AOV can mean higher margins. Each eCommerce order contains baseline costs: ad spend, shipping, and possibly a new customer discount. Once a customer lands on your website and decides to purchase one item, any additional items will add to your revenue. If you’ve drawn a customer in with a discount, convincing them to add a full-price item will greatly improve your margins. 

4. Understand channel profitability

In addition to calculating your overall AOV, run calculations to compare AOV between channels. If you sell on a marketplace like Amazon or Etsy, for example, compare each channel against direct sales through your website. 

You can also run calculations to contrast AOV and profitability between different advertising sales channels. For instance, you may find that Instagram ads cost double your Google search ad campaigns. But if the users coming from Instagram have a higher AOV than Google shoppers, the higher spend is justified. 

5. Get insight into buying trends and patterns

Tracking your AOV helps you predict patterns and trends that impact your operations. The biggest pattern you should be tracking is seasonal swings. For instance, you may expect higher order amounts in Q4 for holiday sales. Jewelers or chocolate sellers may experience a spike in February for Valentine’s Day. By forecasting when customers will have a higher AOV, you can plan your revenue and staffing accordingly.

You should also run analyses on orders with the highest order values to uncover any trends. Did they happen at a certain time of day? Was there a particular promotion that led to higher orders? 

What is a good AOV?

There’s no universal number for a good AOV. The AOV for a gaming app can’t be compared to a grocery order, which can’t be compared to a luxury jewelry website. Location, market positioning, and other factors make it difficult to compare yourself with other merchants.

That said, marketing insights provider XP² has identified some basic benchmarks you can reference to find an overall benchmark by industry: 

• Home & furniture: $248
• Fashion, accessories & apparel: $142
• Food & beverage: $94
• Multi-brand retail: $84
• Beauty & personal care: $80

AOV varies by location. Interestingly, purchases made from desktop computers have a higher AOV than mobile purchases. Think about it: you might casually order a book or some socks from your phone while you’re on the bus, but when it comes to investing in a new laptop or washing machine, you probably want to get comfy and do your research on a bigger screen. 

When benchmarking, remember that the most important comparison point you have is yourself. Work to improve your own AOV relative to previous time periods, instead of worrying about external benchmarks.

How to increase AOV

AOV is a powerful metric that offers insight into customer behavior. But tracking your AOV is more than just knowledge — once you know your average, you have the opportunity to grow it. While there are many strategies for increasing AOV, they all boil down to two goals: encouraging customers to buy more products and spend more on products. 

Here are seven strategies you can employ to grow AOV — and with it, your business.

Upselling

Upselling is the practice of selling a premium or more expensive product shortly before a customer completes their purchase. If a customer has a coffee maker in their cart, for instance, you might suggest the next model up, which includes an espresso machine. Each eCommerce platform has its own way of displaying upsells on a product page or checkout flow.

Cross-selling

Instead of replacing a desired item with a higher-value one, cross-selling lets you suggest complementary products as an add-on. So alongside a coffee maker, you might suggest coffee filters. Some eCommerce sites accomplish this through recommended items on a product page or in the checkout flow itself. You can link recommended items in the back-end of your online store, or even use personalization for successful cross-selling. 

Bundling

Bundling helps you grow AOV by getting customers to buy more products. Instead of selling products, X, Y, and Z individually, offer them as a bundle. Continuing with the coffee machine example, you could offer an espresso machine with a milk frothing pitcher and a grinder to give the complete setup to start making espresso drinks. 

There are several reasons customers like bundles. One may be because there’s a slight discount and price advantage to buying them together. Another reason is perceived value: there’s a convenience to buying multiple items that you need or want that go together, and it saves them time shopping.

Free shipping (with an order minimum)

Free shipping doesn’t help your margins for a small order, but can create an incentive for customers to place a larger order. A Shopify study found that people spend $22 more per order with free shipping over paid shipping, and that they order 2.5 items per order with free shipping compared to less than two items without. 

The key to success with this strategy is strategically choosing an order minimum that’s above — but not too far above — your AOV. For instance, if your AOV is $60, you may want to choose an order minimum of $75.

Applying a percentage discount

Just like with free shipping, you can use a percentage discount to incentivize bigger spending. For example, spend $100, get a 15% discount. If your AOV is $70 and you can convince customers to spend $100 instead, you’re still bringing in more revenue even with the discount.

Loyalty programs

A loyalty program gamifies shopping by offering rewards relative to how much the customer spends. The most effective loyalty programs give transparency into how close someone is to a reward and send offers and reminders to encourage spending. Take Starbucks’ loyalty program, for instance: customers can view their Star balance at any time and take advantage of special offers to double their points earned. 

Customer service programs

While it might seem like customer service and order values are unrelated, they’re more closely connected than you think. 

Making a purchase, especially for a customer new to the brand, represents a risk. Customers don’t know if the quality will hold up to their expectations, and may start with a small first order or abandon the process completely. Having customer service easily accessible by chat to answer questions allays their concerns. A responsive customer service department gives people the confidence to order more items, knowing you’ll be there for them if they’re unhappy.

Frequently asked questions

Key takeaways

AOV (average order value) is a crucial eCommerce metric that shows the average value of orders placed by customers over time. By tracking and optimizing this number, you can boost your revenue and improve your margins.

• A higher AOV translates into higher revenue and improved customer lifetime value (LTV).
• AOV gives you insights into buying trends and lets you analyze channel profitability.
• A good AOV varies across industries and locations. Instead of benchmarking against competitors, focus on increasing your own AOV each month.
• AOV can fluctuate based on seasonal patterns and events. Recognizing these trends allows you to forecast revenue and adequately prepare for changes in customer behavior during peak periods, such as holidays or special events.
• Strategies for boosting AOV include upselling, cross-selling, bundling, free shipping, discounting, loyalty programs, and customer service.
• With AOV optimization strategies, you can incentivize customers to buy more items and spend more overall.

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Purchase frequency is the average number of times a customer orders from you in a set period.

What is purchase frequency?

Purchase frequency is an eCommerce metric that tells you how often customers buy from you in a set period. Many retailers monitor purchase frequency by quarter and by year. While the expected purchase frequency is different for a pair of shoes than it is for a car, tracking this number enables you to benchmark your performance, identify seasonal patterns, and forecast future sales. 

How to calculate purchase frequency

To calculate purchase frequency, determine the time period you want to analyze then use this simple formula:

The key here is tracking unique customers, not the total number of customers. For instance, say you have an online pottery shop and processed 50 orders in Q2 from 35 unique customers. 25 customers each made a single purchase, while 10 customers accounted for the remaining 25 orders. In this case, the purchase frequency would come out to 1.43 — in other words, the average customer placed 1.43 orders in Q2.

How to track unique customers

Of course, to calculate this number with accuracy, you need a way to identify repeat customers. While this can be difficult in a brick-and-mortar business, it’s easier in eCommerce because you have a built-in way to collect identifying information. As a gold standard, encourage customers to create an account with you to track their purchases.

Even when they use guest checkout, you can add customers to a customer relationship management (CRM) database each time they make a purchase, so you can track unique customers by their email address. Another option is to use AdTech to track online shoppers by their IP address. 

If you use point of sale (POS) in addition to eCommerce, encourage customers to enter their phone number, email address, or other identifier to merge your data.

Why is it important to measure purchase frequency?

Purchase frequency is important because it’s a key indicator of customer retention – how often customers return to buy again. Customer retention is a good sign that customers are happy with your products or services and that they’re building buying habits. It’s also far cheaper to incentivize past customers to buy from you than to acquire new ones. 

Here are three ways purchase frequency can help your eCommerce business: 

1. Understand purchasing behaviors

Do repeat purchases happen at a certain time of year, or on a certain day? Is a particular promotion or marketing channel leading to repeat purchases? Tracking your purchase frequency for different variables like these illuminates patterns to help you understand what’s bringing customers back.

2. Analyze product performance

You can drill down further by measuring the purchase frequency for each product or product category. Identify which products are bringing customers in the “door” to buy again and again so you can put more resources into promoting those products. 

3. Boost customer retention and profitability

Once you know your number for purchase frequency (and how it changes throughout the year), you can get to work optimizing it. For example, if you identify a segment of customers with high purchase frequency, you can create loyalty programs or offer personalized discounts for them to encourage repeat purchases. Since customer retention costs less than customer acquisition, this approach can save you money and boost your profits. 

Purchase frequency vs repeat purchase rate (RPR)

Another eCommerce metric similar to purchase frequency is repeat purchase rate (RPR). RPR measures what percentage of your customers make a repeat purchase in a set period. Here’s how to calculate it:

While both metrics measure customer retention, purchase frequency tells you more about the scale of repeat purchases and their potential value. 

Let’s say that you’re comparing two online pottery shops. Shop A has a 50% RPR, as half of its customers came back to place a second order that year. Shop B also has a 50% RPR, but has an extra loyal fan base, and returning customers placed an average of three more orders that year. By these metrics, Shop A has a purchase frequency of 1.5, while Shop B has a purchase frequency of 2.5.

What is a good purchase frequency?

As with most things in life, “good” depends on a number of factors. Purchase frequency varies extensively depending on the industry. Purchases like groceries or coffee are frequent and follow weekly or even daily habits. Large purchases like airline tickets, furniture, or a car might happen just once a year or even less – but that doesn’t mean they’re less successful. Mid-line retail items like apparel and gifts often experience seasonal swings. 

A study by customer retention platform Beans found the following benchmarks for eCommerce brands by category:

• Books, music, & education: 4.5 (purchase frequency per year)
• Pets: 4.49
• Electronics: 4.17
• Vaping & e-cigarettes: 3.96
• Home & leisure: 3.64
• General goods & supplies: 3.5
• Fashion: 3.25
• Food: 3.12
• Toys & hobbies: 3.04
• Beauty & cosmetics: 2.81
• Sport: 2.46

Ways to increase your purchase frequency

Looking for ways to optimize your purchase frequency? Try these five tactics to encourage customers to buy again.

1. Loyalty programs

One way to encourage customers to make more frequent purchases is through loyalty programs. Used by global brands including Marriott, Sephora, Starbucks, and H&M, these programs reward customers for repeat business, often offering exclusive discounts, reward points, or special promotions. By giving incentives for continued purchases, you can nudge customers to buy a familiar brand. 

2. Diversified product offerings

When analyzing which products to add to your store, it’s important to consider whether your products are necessities or discretionary items. When offering a necessity like dog food, you’re limited in how frequent your orders will be because dogs only eat so much food. With consumer goods and luxury items like dog toys or clothes, however, you can increase both your order frequency and your average order value (AOV). 

Offering basic items can anchor your purchases by bringing customers in to buy what they need; then you can promote add-ons with cross-selling. Basic items are also typically recession-proof: dog owners will continue buying dog food no matter the economic conditions, whereas they might skip the dog costume when budgets are tight.

3. Personalization

Personalization is another powerful tool to increase purchase frequency. With today’s marketing technology and the ability to segment and tag audiences in a CRM, it’s easy to create personalized offers and communications for customers. 

Here’s an example: say you sell makeup online and you know the typical bottle of foundation lasts 12 weeks. You can set up an automated email journey to send to buyers 10 weeks after making a purchase with the message, “Running out of X product? Refill today with 10% off”. 

By tailoring offers and recommendations based on individual customer preferences and past purchasing behavior, businesses can create a more personalized shopping experience. This not only enhances customer satisfaction but encourages people to buy more frequently.

4. SMS and email marketing

Out of sight, out of mind. When your brand doesn’t stay visible, customers aren’t likely to remember your product and buy again. Retention campaigns through SMS and email are effective at driving repeat purchases through customer engagement. 

Create newsletters, social media channels, and SMS campaigns to engage existing customers with your brand. Don’t just make your content about the products: add value to customers with practical tips, customer stories, and videos that will give them a reason to follow along. 

5. Subscriptions

Lastly, subscriptions offer a convenient way for customers to regularly receive products or services they need on a recurring basis. Programs like Amazon Prime Subscribe & Save popularized this approach, and now consumers are embracing subscriptions for everything from coffee beans to craft kits to toilet paper. 

The beauty of subscriptions is that once you’ve sold it, it’s essentially passive income: you have a guaranteed number of orders until renewal time. With month-to-month subscriptions, your potential number of orders is unlimited. 

By offering subscription options with added benefits such as discounted pricing or exclusive access to new releases, businesses can ensure regular revenue streams while increasing purchase frequency.

Key takeaways

In summary, purchase frequency is an essential metric for eCommerce businesses looking to increase retention and drive growth in today’s competitive market. 

Here are the key points to remember:  

• Purchase frequency is an indicator of customer retention, a valuable way to grow your revenue without the high price tag of new customer acquisition.
• Measuring your purchase frequency gives you valuable insights into customer behavior and buying patterns throughout the year: knowledge you can use to optimize and grow your sales.
• The typical purchase frequency varies wildly by product category. Frequency tends to be lower for luxury items and apparel, and higher for consumables and essential items. 
• Loyalty programs are a great way to track customer behavior and incentivize repeat purchases, while a subscription model ensures a steady income from loyal customers.  
• It’s important to offer a range of products, from essentials to discretionary items. When you track purchase frequency for different product categories, you can identify, add, and promote high-frequency products.
• Offers and discounts are a great way to encourage repeat orders. Take your promotions to the next level with personalized offers, and craft SMS or email campaigns to give your customers relevant offers with a VIP feel.

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Attribution modeling is a way of measuring how effective marketing campaigns and channels are at influencing people to take a desired action (such as making a purchase).

What is attribution modeling?

Attribution modeling is a way of measuring the impact of different marketing efforts across the customer journey, so that advertisers can assess which channels or campaigns are most effective in driving conversions. 

As they engage with a brand, users are exposed to various marketing touchpoints — both paid and organic — which can influence them to take a particular action (installing an app or making a purchase, for example). Attribution models analyze interactions with these touchpoints, and work out their contribution to the decision-making process. 

Attribution modeling can be single-touch, analyzing the effectiveness of a single click, or multi-touch. Multi-touch attribution models (MTAs) help marketers understand how consumers make decisions across multiple brand engagements over time.

Why is attribution modeling important? 

Attribution modeling gives marketers vital insight into what’s working and what’s not in their campaigns. If you don’t understand where your leads and sales are coming from, you may continue to invest in ineffective channels and lose out on potential revenue.

What are the benefits of using attribution models? 

When you understand which campaigns are driving user engagement, you can double down on what’s working and increase your ROI. Let’s take a closer look at some of the benefits of attribution modeling. 

1. Better resource allocation

Attribution modeling helps you allocate your marketing resources more efficiently. You can shift budget and effort away from underperforming channels, reducing waste, and towards those that have a higher ROI and greater impact on conversions.

2. Agile decision-making

Attribution modeling helps you make smart, data-driven decisions about your marketing efforts in real time, so you don’t waste a cent of your budget. Instead of making decisions at the start of a campaign and assessing monthly or quarterly, you can test and adjust messaging quickly based on immediate results. Some tools can even A/B test content and automate allocation based on results. 

3. Personalization

With cross-device tracking, you can understand the customer’s previous interactions and behaviors. Use these insights to create personalized marketing experiences, leading to more engaged, loyal users and increasing the chances of conversion.

What are the different attribution models? 

There isn’t just one attribution model to assess your campaign’s effectiveness – there are many. 

Because each customer’s journey can involve multiple touchpoints in the buying process, marketers need to decide which touchpoints have the most influence on the conversion.

Single-touch attribution

The simplest attribution methods are single-touch — in other words, they measure the impact of one particular touchpoint in the customer journey. 
First-click (or first-touch) attribution assigns the credit for each conversion to the first interaction the customer had with a brand, like clicking on an ad or social media content. Last-click (last-touch) attribution, on the other hand, credits the last interaction before the conversion.

For example, let’s say a user discovers a product through an organic Google search and later makes a purchase after clicking on a paid advertising banner. A first-click attribution model would attribute the conversion entirely to the organic search, ignoring the influence of the paid ad. A last-click attribution model would attribute the conversion entirely to the ad, ignoring the influence of the earlier touchpoints like organic search. 

While first-click and last-click attribution provide straightforward ways to assign credit, they can oversimplify the customer journey by ignoring other interactions and touchpoints that may have played a crucial role in the conversion process. 

Multi-touch attribution (MTA) models

MTA models, such as cross-channel or time-decay attribution, aim to provide a more holistic view of how different marketing channels contribute to conversions by considering multiple touchpoints along the customer journey. These models can offer a more nuanced understanding of the customer’s path to conversion and help you allocate resources more effectively across various channels.

Here’s an overview of the different attribution models and how they work:

What are the challenges of attribution modeling?

Attribution modeling is a powerful tool for marketing teams, but putting it into practice can be complex. 

Industry changes, particularly in the area of privacy, are posing challenges for attribution modeling and eroding the data available to companies. Overcoming these challenges requires a combination of technology, data governance, and ongoing refinement of attribution methodologies to better align with evolving customer behavior and business goals.

These are the top four attribution challenges facing marketers today — along with some possible solutions:

Data accuracy

Since attribution modeling relies heavily on data, inaccurate or incomplete data can lead to misattribution. Ensuring that data sources are clean, reliable, and consistent can be a significant challenge.

Solution: Put data governance in place in your company to apply best practices and expertise. Make sure you have a trained data analyst on your team, or ask an internal or external consultant to audit your data collection processes. 

Data integration

MTA and cross-channel models can provide a more accurate picture of how marketing efforts contribute to conversions because they acknowledge the complexity of the customer journey. However, integrating data from these disparate sources can be complicated: data needs to flow seamlessly from multiple sources and be properly mapped to customer journeys.

Solution: A UK report found that two-thirds of marketers don’t believe they have the right tools to support cross-channel attribution. To help you, work with an analytics platform like AppsFlyer that specializes in data integration across channels. 

Cross-device tracking

According to an eMarketer report, cross-device tracking is the second-largest (42%) attribution challenge for marketers. Customers often switch between devices ( like desktop, mobile, and tablet) during their journeys. Tracking these cross-device interactions accurately can be challenging, as cookies and identifiers may not always work seamlessly across devices. 

Solution: Implement AdTech solutions that recognize users based on identifying factors like email address, matching IDs, or cookies. 

Privacy and compliance

Stringent regional privacy regulations such as GDPR and CCPA limit what user data you can collect and use. Apple’s ATT framework and Google’s plans to eliminate cookies also restrict what data you can track.

Solution: Rely more heavily on first-party data, such as directing users to your website or app or incentivizing them to opt in as a subscriber. You can also start using privacy sandboxes to proactively address this problem in mobile advertising. 

How to choose the right attribution model for your business

Just as customers can take more than one journey to find your product, there’s more than one right way to measure attribution. When it comes to choosing an attribution model, the first decision you need to make is between single-touch and multi-touch attribution. 

An MMA report found that a majority (53%) of companies used multi-touch attribution models in 2022. Companies that use MTAs are more satisfied (70%) with their ability to measure the effectiveness of marketing spend than those that don’t (42%). Most MTA users (63%) are better able to immediately apply their learnings, versus those using single-touch (51%). 

While MTA has clear benefits, it remains more difficult and more expensive to implement. Many companies remain in an adoption phase, with only 27% of companies saying they’re at full MTA deployment. 

If you decide to go down the MTA route, you need to select a specific model such as linear, W-shaped, or U-shaped attribution. You should choose a model that aligns with your company’s goals, data availability, and understanding of customers’ behavior. 

Here are four factors to consider:

The customer journey

How complex is your product and buying journey? A widely-recognized consumer product will have a completely different customer journey than a B2B service or software with multiple steps and decision-makers.

Sales cycle

How long or short is your sales cycle? U-shaped attribution is good for measuring short sales cycles, while W-shaped or linear models may capture the nuances of longer cycles.

Offline factors

If offline advertising such as direct mail, TV, or out-of-home still forms an important part of your marketing strategy, MTA will paint a limited picture. While you may be able to collect some data relating to these channels, you’ll need to consider if it’s possible to integrate it with online data. 

Company size and resources available

Of course, staffing and budget will always play a role in decision-making. Small companies may not have the skill or time in house to implement MTA. They also may not have the budget to invest in agencies, adtech, or comprehensive measurement tools. However, the more you can measure, the easier it will be to demonstrate marketing ROI and make wise use of shoestring budgets. 

How to measure results

As we’ve covered, there’s a range of approaches and tools available to measure attribution. Whether you want an out-of-the-box solution or complete customization, here are three ways you can measure and attribute results for your campaigns:

Google Analytics 4 (GA4)

GA4 is the most popular web analytics tool on the market. A free tool, it can integrate data from both websites and apps, and from paid and organic campaigns. Features include multi-channel funnels and attribution reports that offer insights into how different marketing channels and touchpoints contribute to conversions. The default attribution model on GA4 is “last interaction” (last-touch), but you can switch to several alternatives. 

While GA4 is a powerful tool, integrating GA4 with non-Google tools and platforms can pose a challenge. 

Third-party attribution

When integrating data from a variety of sources, a third-party attribution system can be valuable. These are external tools, platforms, or services that give a more independent and comprehensive view of your marketing performance. For example, a third-party attribution tool can seamlessly integrate real-time analytics from multiple advertising sources. Look for features like cross-channel tracking, deep linking and in-app analytics, audience segmentation, and fraud detection. 

Creating your own tool with Python

If you’re looking for a custom analytics tool, you could choose to build your own in Python. Building a custom tool is a complex undertaking, but is possible with the right knowledge and tools. A developer will need to collect and prepare the data, choose an attribution model, process the tool through a Python library, and apply the model to the data with visualization and custom reporting.

Key takeaways

• Attribution modeling is a way of measuring the impact of marketing activities across the customer journey. The models analyze customer interactions with various touchpoints, and work out how much each has contributed to the conversion. 
• Effective attribution modeling shows marketers what’s working and what’s not. It offers insights that enable better decision-making, resource allocation, and personalization.
• The key challenges marketers have to overcome with attribution modeling are data accuracy and integration, cross-device tracking, and privacy concerns. 
• While multi-touch attribution (MTA) gives a fuller picture than single-touch, it’s more complex to implement.  
• There is no one-size-fits-all solution to attribution modeling. Consider your sales cycle and customer journey, resources, and goals when choosing a model.
• Consider your overall marketing mix and strategy when choosing an attribution tool. Depending on your needs and resources, you can opt for a free, out-of-the-box tool, a third-party provider, or a DIY approach. 

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