What is context and how should enterprise brands use it?

In case you haven’t heard, we’re now living in the Context Economy, where a brand’s success is determined by how intelligently they adapt to what their customers want.

This makes context the most valuable currency in business. But what is context, exactly? Where does it come from? And how should brands use it to address buyer needs in the moment?

What is context?

Context is the full story of what each buyer is trying to solve, based on their interests, historical behavior and real-time engagement.

It’s more than who the customer is, it’s why they decided to visit your site on a given day or engage with other digital touchpoints.

Context is extremely valuable because it allows your marketing team to stop guessing at what your customers want. When you have quantifiable data about a specific buyer’s needs as well as the ability to create content and offers for them in real time it enables your team to deploy 1:1 personalized experiences to individuals at scale.

Remember: Buyers prefer personalized experiences and many are even willing to pay extra for those experiences. But until you can effectively capture and deploy context, you’re stuck with marketing to broad personas and use-cases — a traditional approach that is becoming less effective as customer demands for hyper-relevant experiences increase.

The 11 types of context

So what contextual data should you be trying to collect when a potential buyer lands on your site? Here are 11 forms of context that you may already be collecting with your DXP or CDP.

1. Content interests

Every digital interaction is your customer telling you what they are or are not interested in — but you might not be listening well enough. By gathering information about their interests (think: their favorite product types or topics), you can serve the buyer similar content during their next visit to your site or deliver it to them through other owned channels such as marketing emails.

2. Audience membership

Does a site visitor already subscribe to one of your newsletters? Have they previously made a purchase, or signed up for a demo of your software? Have they downloaded your content in the past, and if so, which content? Audience membership information about known visitors allows you to deliver them highly relevant content based on their position in the sales cycle or favorite topics.

The next nine attributes are critical to developing behavioral scores in Contentstack’s Data & Insights platform:

3. Quantity

This measures a user's cumulative activity over their lifetime of engagement with your brand, relative to all other users. The more activity the user registers, the more engaged they are.

4. Frequency

How often does a user interact with your brand over time? Do they visit once a day? Once a week? Once a year? Frequency serves as a measurement of user regularity. Targeting your most frequent users can be far more effective than targeting "users who visited in the last week," for example, which can pull in a wide mix of highly engaged and barely engaged visitors.

5. Recency

This reflects how recently a user has had an interaction with your brand, compared to their past activity. Recency can give you insight on buyers who are floating away from your brand and may need additional nurturing, or new buyers who may finally be ready to purchase.

6. Intensity

The behavior a user exhibits during a single session is very telling of them as a consumer. If they have high interaction in a session (high intensity) they are more likely to be a deeper researcher or more curious. If they have low interaction in a session (low intensity) they are more likely to be casually browsing or engaged with a certain piece of content, but not your overall brand.

7. Momentum

This measures the rate at which a user is interacting with your brand; in other words, the user's recent activity relative to the user's past activity. It can be easy to confuse momentum and recency, but they’re actually very different. Recency measures absolute recency of activity, but just because a user has recent activity, doesn't mean they're showing purchase behavior or not a churn risk.

8. Propensity

There are many reasons why users churn, but from a data perspective, attrition of any kind starts to look similar. Propensity predicts how likely a user is to return based on positive interaction patterns. 

This measurement employs statistical models to identify any patterns for detecting how and when attrition starts to occur. With time, you can find more patterns in your data and become increasingly accurate in identifying when users start to exhibit those behaviors.

9. Consistency

This measures the regularity or stability of a user's engagement pattern. For example, a user that registers behavior every seven days will have high consistency compared to a user that interacts with your brand every 30 days. 

Consistency scores can be paired with propensity scores to build more accurate Lookalike Models to predict customer churn and target users with win-back programs before they bounce. 

10. Maturity

Maturity is a measure of how long a user has registered behavior. This indicates how "old" a customer is relative to your other users. A user who has registered behavior over five years will likely have high maturity. A user who registered behavior over three years, but hasn't registered any in two years will have less maturity.

You could target high maturity users by inviting them into a loyalty rewards program via ads, emails and in-app notifications. Low maturity users, on the other hand, could be served more onboarding or educational content to nurture them into high-value, long-term users.

11. Volatility

And finally, volatility measures how stable vs. sporadic a user's behavior is while interacting with your brand. It represents the stability of the volume of data that a user is generating, and serves as a slightly more nuanced version of the intensity measurement.

How to start gathering context in Contentstack

Contentstack Edge users have access to Data & Insights, a real-time intelligence engine that captures visitor interactions as they happen and connects your content with live user behavior to make every visit more relevant and impactful.

To gather context and put it into action with Data & Insights, follow these six steps:

Step 1: Enable the Data Activation Layer

To establish a connection between Contentstack and Data & Insights, you must first enable the Data Activation Layer (DAL). DAL acts as the central hub linking Contentstack (CMS), Data & Insights for behavior tracking and Personalize (delivery). It authorizes data flow across platforms.

By enabling the Data Activation Layer (DAL), you can connect audience behavior directly to personalized content in your stack, allowing you to adapt homepage messaging, optimize landing pages and tailor marketing journeys based on what users care about most, in the moments that matter.

Read more: Create a Data & Insights Integration

Step 2: Enable and install the JavaScript Tag Plugin for Contentstack

The Data & Insights Js Tag collects real-time behavioral data (page views, clicks) and sets visitor cookies for audience segmentation. This tag is the foundation of behavior-based audiences; without it, no data is collected and personalization cannot occur.

For full instructions on how to install the tag, go here.

Step 3: Set up Content Sync to import CMS entries and taxonomies

Content Sync imports your Contentstack entries and taxonomies into Data & Insights so content can be analyzed and scored. Without syncing content, Data & Insights (Lytics) cannot build topic-based profiles or recommend relevant content.

Use this guide to score visitors based on the topics they consume, and refer to our Topics and Affinities documentation for more guidance.

These first three steps are simple to complete, and will give you all you need to gather context and begin drawing insight from it. The next three steps listed below take a little more work, and will allow you to personalize experiences with context.

Step 4: Create Data & Insights Audiences and Personalize experiences

Use the content affinities generated from Content Sync to build meaningful audience segments within Data & Insights. These segments are then synced to Contentstack Personalize, where you can create tailored experiences based on audience behavior and interest.

Data & Insights uses content interaction data to assign users to audiences, and Personalize uses those audiences to deliver targeted Entry Variants. Without defining audiences, you won’t be able to personalize content based on user behavior. This step is the bridge between raw behavior and tailored content delivery.

Step 5: Integrate Personalize With Your App

Use the SDK or custom middleware to fetch variant data specific to users for server-side rendering. If you need direct programmatic control over variant injection into pages, this step is required. Otherwise, variants may be served automatically based on cookies.

To get Personalize up and running in your app, please use one of the Setup Personalize Guides.

Step 6: Validate the setup

Final validation of your setup can be viewed in the Audience Preview within the Visual Builder and Timeline that you have configured. In Personalize, you can view the Impressions and Conversions (for A/B Test experiences only) for each of your experiences within the Experience Analytics.

Our team will be happy to work with you to get these foundational steps set up so you can begin offering personalized experiences on your site. Book some time with us today to start digging in!