Adding Activation Opportunities
Adding activation opportunities is essential for Context Decision to deliver maximum value to you — learn why it’s required and how to implement them.
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Adding activation opportunities is essential for Context Decision to deliver maximum value to you — learn why it’s required and how to implement them.
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Was this helpful?
When integrating Context Decision, it's crucial that you increase the activation opportunities in your app, in order to increase the number of sales and revenue.
Consider a scenario where your app displays an upsell prompt after a user completes a key positive action, such as signing up. If this prompt is shown universally — without considering the user’s real-life context — you may be missing opportunities to optimize its effectiveness. For example, if 100 users sign up, the prompt is shown 100 times, and the conversion rate is 10%, you achieve 10 sales.
Now, imagine integrating ContextSDK into this flow. By displaying the prompt only in the top 50% of moments — based on the user’s real-life context — your conversion rate improves to 16% (an example, just to illustrate). However, since the prompt is only shown 50 times now, the total number of sales decreases to 8. While the conversion rate is higher, the reduction in prompts results in fewer overall sales. If your primary goal is to generate more revenue, showing fewer prompts — even with higher conversions — may not achieve that objective.
This highlights the importance of identifying and adding new activation opportunities. By assessing additional points in your app where a user’s context can be evaluated, you can decide whether to display an upsell prompt. For example, you could introduce a new upsell moment after another key positive action in your app. By pairing these new moments with A/B testing, you can ensure that both control and treatment groups receive the same number of prompts, while ContextSDK optimizes the timing to display them only during optimal moments. This approach ensures you maintain or increase the total opportunities to generate revenue, while leveraging ContextSDK to improve the user experience.
There are two types of activation opportunities:
Opportunities that refine existing algorithms, leveraging ContextSDK’s ML decision-making to enhance or completely replace the logic previously used to trigger your upsell.
Example: a dating app currently shows an upsell prompt once every 10 profile swipes. We could tweak this number to 1 every 5, 1 every 2, or even on every swipe. See Won't this annoy the users even more by spamming them?
Opportunities that introduce new triggers, expanding the potential for upsells by incorporating additional moments into your app.
Example: an app shows an upsell prompt on every app launch. In this case there's no way we can increase the number of prompts shown, because it's already shown on every app launch (being as annoying as possible). In this case we'd need to introduce a new opportunity somewhere else, e.g. every time the user completes a key positive action within the app, tailored to the app’s specific industry.
First, determine whether the flow you’re enhancing with ContextSDK already uses existing algorithms, as shown in the first example above. If it does, that’s great news — it’s the easiest to refine and improve. If your current flow aligns more with the second type, you’ll need to explore new user journeys in your app where adding an upsell opportunity makes sense. These opportunities often arise after key positive interactions or in other carefully timed moments.
After identifying where to introduce new activation opportunities, collaborate with our technical team to configure a model tailored to this new flow. Ensure this configuration is complete before rolling out the new flow to production.
Not at all — that’s the strength of ContextSDK’s ML models. These models naturally reduce the number of prompts shown by focusing on the most optimal moments. However, to maintain the same overall prompt frequency as before, it’s essential to introduce new activation opportunities. If these two actions — refining prompt timing and increasing opportunities — aren’t implemented together, you risk either reducing the total number of prompts (potentially decreasing revenue) or increasing them unnecessarily (which could frustrate users). For the best results, these steps should occur simultaneously: deploying the ML model and adding new activation opportunities.
During the calibration phase, we recommend the new activation opportunities to be "live", but disabled. There are 2 ways to disable them during the calibration phase:
Inform us which flows are the new ones that should be disabled, and we'll disable them remotely by always sending shouldUpsell = false to your flow, during the calibration phase.
Check if the model info exists and update your implementation accordingly:
It depends on your current prompt volume and your ability to increase it through existing and new flows. This directly impacts your conversions, so careful planning and understanding of your application is key.
For example, if your current flow generates 10,000 prompts per week and you can add another 10,000 activation opportunities through new or refined flows, you effectively double your activation opportunities. By setting the prompt intensity for both flows to 50%, you would still display a total of 10,000 prompts per week — maintaining the original volume — but now only during the 50% best moments. See the chart below for an illustrative relationship between prompt intensity (percentage of prompts shown) and potential conversion rate improvements.
To achieve this, evaluate your app’s unique use cases and user behavior. New flows or refinements to existing ones may unlock the additional opportunities you need. For instance, you could introduce 10 new flows, each contributing 1,000 prompts per week, or a single high-volume flow adding 10,000 new opportunities. Similarly, refining existing algorithms can further optimize your results. In a dating app, for example, a prompt currently shown every 10 profile swipes could be adjusted to evaluate the context every 5, every 2, or even every swipe. By leveraging ContextSDK’s ML decision-making, you can ensure prompts are displayed only at the most effective moments, striking the right balance between volume and impact.
Activation opportunities refer to moments when your app invokes ContextSDK to capture and analyze the user’s context. These moments allow the ML model to determine the next action — such as displaying an upsell screen, presenting an ad, skipping a flow, or other contextually relevant actions — tailored to your app’s specific use case.
