Fundamentals of Data-powered Messaging

This is part 1 of a 5-part series titled Data-powered Messaging For True Personalization – powered by Piwik PRO.  

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Let’s begin with a thought exercise. 

You’re browsing LinkedIn, you see a post about a tool meant to solve a problem you’re looking to solve, and decide to give it a try. You create an account and start poking around, and within a few minutes, based on your tinkering, you’re either convinced that you need this product or you need to tinker some more, in which case, you decide to return to it later.

Now, take a look at the following welcome emails that you can potentially receive from the product you just signed up for. 

Option 1: A welcome email that talks about the team’s excitement that you decided to try their product and describes how to get started, it looks like this:

Option 2: A welcome email that acknowledges what you have done so far in the app and mentions the next best action for you to begin deriving value from the product, it looks like this:

Which welcome email do you find more engaging?

The answer is obvious, isn’t it?

Option 1 is part of a linear campaign whereas option 2 is from a data-powered campaign. 

Linear vs. Data-powered campaigns

All messaging campaigns across channels – email, SMS, push notifications, etc – are either linear or data-powered. 

In a linear campaign, every user, irrespective of their actions, receives the same set of messages as they move through the campaign. And every message is delivered as a broadcast with a predefined delay between messages. 

On the other hand, messages in a data-powered campaign are delivered based on a user’s actions or the events they perform while using the app. Every message is based on a trigger – a set of predefined conditions to decide whether the message is to be sent to a user or not. 

A message trigger includes one or more events a user has performed, combined with one or more events the user is yet to perform in the app. For example, one might want to send a message to users who have created an account but haven’t verified their phone number within 24 hours. 

Besides events, triggers can also include event properties as well as user properties. Event properties will come handy if you want to trigger messages only for, say, users who perform an event on a specific page or screen of your app. And user properties are useful if you want to trigger messages only for, say, users of a specific age group. 

In terms of delivery, a message, once triggered, can be delivered either immediately or after a predefined delay like a few hours or even days. Now, when a delay is specified, It’s the responsibility of your messaging tool to check the trigger conditions once again before delivering the message. Doing so ensures that a user receives the message only if they meet the trigger conditions at the time of the message delivery. It’s possible for a user to perform – during the delay – the action that the message would ask them to perform, in which case it makes no sense for the user to receive that particular message. This is an important thing to keep in mind and one should ensure that their messaging tools support this capability.

Finally, the contents of the messages can be further personalized by alluding to user actions – mentioning something a user has done right in the message body, resulting in higher relevance and therefore, more engagement. 

To summarize, in data-powered campaigns:

• A message is triggered based on the combination of something a user has done and something the user is yet to do.
• Two users who enter a data-powered campaign at the same time, can receive completely different messages at different times. 

Before moving on, it’s also worth highlighting that data-powered is not the same as dynamic, and a linear campaign is not necessarily static. The terms dynamic and static refer to the message body whereas the terms data-powered and linear refer to the mechanism used to deliver messages.

For instance, messages in a linear campaign can contain dynamic content such as a user’s name or any other piece of data shared by a user directly. I specify “data shared by a user directly” because unless the campaign is data-powered, it doesn’t make any sense to include user actions in the message body. 

Why? 

Well, when a message in a linear campaign refers to a user action, it’s merely an assumption that the user has done that thing because there’s no trigger that checks if the user has actually done that thing. 

The first step toward delivering relevant, engaging messages is to make no assumptions about what a user has or hasn’t done in the app. 

How can you identify a data-powered campaign?

The next time you sign up for a new app, whether at work or for personal use, try the following to figure out whether the messages you receive – both emails and notifications – are data-powered or not:

1. Do nothing for a day
2. Go back to the app, but leave a key action incomplete (such as completing your profile or setting up an integration) and exit the app
3. Go back the next day and perform all the key actions needed to derive value from the app

You are likely to receive a few messages over the first two days and based on the contents of the emails and notifications, it will be easy to find out whether those are data-powered or linear.

Data-powered messages will refer to the actions you’ve left incomplete and offer a resource like a video or a tutorial depicting how to perform those actions. Once you perform the key actions, the next set of messages will ideally acknowledge the progress you’ve made, nudge you to try new use cases or spend more time in the app, and ultimately, introduce you to paid features.

If you notice that the messages are generic, and only talk about product features without any reference to what you’ve done or not done in the app, those messages certainly belong to a linear campaign. 

For instance, an email asking you to try a product feature after you’ve already tried it. How often do you receive such messages? Pretty often I bet, especially if you, like me, try new apps all the time.

Next, let’s find out why data-powered campaigns are more effective than linear campaigns.

What makes data-powered campaigns more effective than linear campaigns?

For starters, a message that is triggered based on something a user has done in the app is inherently more personalized because of its relevance and timeliness – it nudges the user to do something they haven’t or acknowledges something they have. 

But that’s not all; there are several direct benefits of data-powered campaigns such as:

1. Data-powered campaigns increase engagement by reducing redundancy and delivering emails only when necessary
2. Data-powered campaigns make it easier to initiate conversations with users, enabling user-facing teams to get to know them better
3. Data-powered campaigns present an opportunity to supercharge persona-based personalization, resulting in truly personalized messages

Let me go a little further into each of these. 

More engagement

The beauty of data-powered campaigns is that they eliminate redundancy by preventing the delivery of messages that don’t add value, thus increasing engagement. 

For instance, as mentioned earlier, a message prompting the user to do something in the app after they’ve already done that thing. Or recommending a product that the user has already bought. These messages clearly don’t add any value and the recipient of such messages is likely to ignore future messages too.

Similarly, data-powered campaigns can help prevent degrading the user experience by, say, temporarily excluding users from all campaigns while they have an unresolved support ticket. These are times when a disgruntled user won’t think twice before hitting the spam button. Think about it – isn’t it frustrating to receive a promotional message from a brand while you’re having a poor experience with their product or service?

It really helps to keep in mind that not delivering a message when it’s redundant is also a form of personalization. 

Conversations

As someone who has designed many messaging campaigns, I can tell you how gratifying it is to receive a response from a user. 

However, do you find yourself wanting to reply to an email that is evidently a broadcast? On the contrary, how likely are you to reply to an automated email that is evidently triggered based on an action you’ve performed, where the email is seeking a response to a relevant question? 

I read and respond to a lot of automated emails (and some broadcasts too) and the likelihood of me responding is much higher when I can tell that the message was triggered based on something I did which means that someone on the other side is likely to receive my response and maybe even act on it to elevate my experience.

Persona-based personalization

Persona data such as role or industry are excellent data points that B2B brands can use to hyper-personalize message content. Similarly, gender, age, and location are useful data points for consumer tech and ecommerce brands looking to deliver relevant offers and recommendations. 

Now technically speaking, persona data only helps deliver dynamic content in the message body. However, next-level personalization is made possible when persona data, (also known as entity data) is paired with product usage data (also referred to as event data). 

This is certainly more work but enables growth marketers to not only craft messages with more relevant resources and recommendations, but also deliver them exactly when they are likely to be consumed and acted upon by the user.

Use this template

Now it’s time for you to act upon what you’ve learned so far so I’m sharing this email template that you can use in your data-powered campaigns:

Hey there,

Thanks for trying {{product_name}} and glad to see that you had a chance to explore it already!

Now go ahead and ___next best action___ to ___benefit___. 

Here's a video walkthrough in case you need help. And if you have questions, please hit reply and send them my way.

Cheers!

Also, you can easily adapt the message for other channels such as SMS or push notifications:

That’s some quick progress! To ___benefit___, ___next best action___. Need help? Here's a video walkthrough.

I hope this guide has been useful and good luck setting up your data-powered campaigns!

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The next part of this series will be live on April 29, 2024. Until then, you can explore the recommended guides below to keep learning.