Adobe Customer Journey Analytics helps customer-centric brands

identify and predict churning customers.

Using a streaming video network as an example,

let me show you how we can find the customer journey issues

leading to churn and proactively mitigate them

before they become a wider problem.

In Analysis Workspace, we can use data

to predict the trend of viewership at the streaming network.

I'll turn on Forecasting,

a feature unique to Customer Journey Analytics,

which uses statistical models

to determine how data will change moving forward.

Looking at the projections, we see that viewership is trending down,

and if things remain the same,

we can expect that subscriptions will steadily decline as well.

Let's dig deeper and find out why.

So far, we've looked at total viewership.

Let's look at what users are streaming and what that can tell us.

Using a freeform table, we can analyze viewer metrics

to see how the various media genres are performing.

Let's see if we can learn anything more by digging into Nature Documentaries.

To quickly understand customer behavior,

we don't have to spend a lot of time guessing and checking the data.

Instead, we'll let generative AI support us

so we can focus on the findings.

Intelligent captions utilize advanced machine learning

and generative AI

to provide valuable natural language insights.

Here, we see that viewership dropped significantly

between May and August.

As we continue assessing key metrics,

like subscriber cancellations,

we can see a correlation

between a decrease in nature documentary viewership

and continued cancellations.

Let's see how we can fix this.

We can try targeting fans of nature documentaries

with a homepage and app takeover.

To determine the best creative to use,

we can run an A/B test in other Adobe Experience Cloud products

like Adobe Target or Adobe Journey Optimizer.

Once the experiment is live,

we'll analyze the results in Customer Journey Analytics

to find out if the campaign boosted Subscriptions

and Media Streams.

The experimentation panel can assess all the testing data

and tie it to any success metric we choose.

The Summary conclusively tells us

that one variation will have a massive lift

with very high statistical confidence.

As the new creative begins to influence customers,

we can trend and forecast again

to see how viewership and subscriptions are impacted.

That's a quick look at how to use forecasting

to identify and predict churn,

and mitigate attrition through testing, assessment,

and data-led decision-making.

Ultimately, we improved our subscription renewal forecast

and reversed several declines with insights

from Adobe Customer Journey Analytics.

It's data analysis at the speed of thought.