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At Aampe, we talk a lot about aligning your app content with your message content, and then aligning your message content with your users preferences, but we always start that talk in the same way: “write a whole bunch of messages.” This isn’t intuitive to many of our customers. They’re used to what we call the “Standard Advertising Design” (SAD) of customer communication, where you segment your customers, make campaigns for each segment, and write a message for each campaign. Maybe, if you’re A/B testing, you write two or three messages for each campaign.
In any case, we find that when people new to Aampe hear “write a whole bunch of messages”, they hear “write a few dozen messages”. What we mean is “write a few hundred messages - at least…better if you can write a thousand or so” We’ve built our Composer tool to make it easy to write a message, break it down into building blocks, then switch out those blocks to create hundreds or, yes, even thousands of messages in just a few minutes…but that’s a topic for another time.
Right now, let’s talk about why all those messages are the first ingredient of a good messaging strategy. This gets a little technical, but don’t worry: there are pictures :)
It’s a matter of credibility
Communication is a huge part of how you build (or lose) credibility with your customers. If you talk to them about what they like, when they like, and in a way that they like, then you’ll build credibility. If you talk to them like you’re a marketing department and they’re just a source of revenue, then you’ll lose credibility.
Aampe uses a large message inventory as the starting point for what we call the Guess-Listen-Adapt Design (GLAD) of customer communication: we take all those messages and find which users they’re best suited for. But for the sake of illustration, let’s assume a world where Aampe doesn’t exist: let’s assume you have no way of aligning your communication with customer’s individual preferences at scale. All you can do is send a message, and it’s a coin toss whether that message will build or lose credibility with each of your users. This results in what statisticians call a random walk - with each message, you either deposit one coin into your user’s credibility bank, or you withdraw a coin. As time goes on, your credibility “balance” for each user depends on how your latest message affected your credibility, and on how your credibility stood before that message.
We promised you pictures, so here you go:
This is the random walk: each blue line is a user, and every user starts at zero. With each new interaction, you gain or lose credibility. Notice what things look like by the end of all those interactions:
- You’ve built lots of credibility with a few users
- You’ve lost lots of credibility with some users
- A whole lot of users are still hovering right around zero, which means they’re still deciding how they feel about you.
If your credibility with a user is below zero, you haven’t convinced them to do anything on your app that would provide value to you - they haven’t bought anything. The more credibility you have, the more they buy. (And remember, we’re pretending right now, just for the sake of illustration, that there’s no way to tilt the randomness in your favor…although that’s exactly what Aampe does).
Eventually (sometimes quickly), users just run out of patience
The problem with this random walk is that your users don’t let you run a deficit forever. Lose enough credibility, and they’ll take their attention and money elsewhere. This is what probabilists call an “absorbing barrier” (Google “gambler’s ruin problem” if you want to dive down that rabbit hole). Essentially, if a user hits the absorbing barrier, their walk stops - there’s no set of next steps in which you can gain back credibility…they’re just done with you.
This is what happens if you have an absorbing barrier:
The red lines show the random walks that got cutoff, because users simply stopped listening. The gray lines show how those random walks would have changed if they’d been allowed to continue. Notice that some of those gray lines rebounded quite a bit: there was value to be had there, but we lost it, because we hit the limit of our user’s patience.
When exploring a new app, the credibility balance each user holds for us has some degree of overdraft protection. You don’t need every message to be perfect. That being said, you can’t get it wrong too many times without getting it right just as often. If you lose enough credibility, you lose your user.
The more you lose credibility, the more you lose value
The longer you can keep a user, the more credibility you can build with them, and the more opportunity they have to provide value to your business. If you have really patient users, then your random walk might look something like this:
You’ll recognize the random walk in the top image, but we’ve added a second picture on the bottom to summarize the total amount of “positive credibility balances” you have at any given moment in time. The blue line is what you would have seen if there had been no absorbing barrier - if every user had been infinitely patient. The gray line is what you actually get, given that some users drop you. There’s not much difference between the two lines. That’s because we set a ridiculously low absorbing boundary (in other words, we imagined that our users were ridiculously patient). Users, in general, are not a patient people. This is a more realistic scenario:
That’s a big gap. The less patient your users are, the less forgiving they are when you repeatedly lose credibility with them.
Message diversity protects you against credibility loss
Ok, so pictures are very pretty, but what do random walks and absorbing barriers have to do with writing lots of lots of messages?
Nothing loses credibility with a user like messaging the same thing over and over and over again. It doesn’t take many messages that all say some thinly-disguised variation of “Act NOW to get 20% off!” before a user decides that you won’t ever have anything new to say to them. They’ll tune you out. And if they tune you out, you have no way to remind them of what you offer them. And if you can’t keep anywhere close to top of mind, then you’ve lost those users.
There’s a lot of uncertainty in customer communication - you might message a user about the exact thing they want (gaining credibility), but at a terrible time for them to act on it (losing credibility). Figuring out the right message and right topic and right time for each user is hard (which is why we built Aampe to make it easy). Limiting yourself to just a handful of messages and recycling those messages over and over again is a sure-fire way to lose credibility. The greater the number of messages you can send at any given time, and the greater diversity of messages that quantity represents, the more likely you are to send each user a message that is different *enough* from what you sent them last time that it won’t automatically lose credibility.
Combine true personalization with message diversity to grow credibility (and value)
So now, let’s stop pretending that every message is a coin toss. Aampe algorithmically matches messages with user preferences to get users what they want when they want it. All of the random walks above assumed that each message had a 50% chance of adding credibility, and a 50% chance of subtracting credibility. Let’s keep the realistic absorbing barrier that we used in the last example, but let’s chance those probabilities just slightly: 55% chance of a message succeeding vs. 45% chance of it failing:
In the previous scenario (50% chance of message success), we ended up missing out on over 70% of our users’ credibility over time because we hit the absorbing boundary and users just stopped listening. In this very slightly improved scenario (55% chance of message success), we miss out on only 30% of our user’s credibility over time, and the amount of credibility we do succeed in stockpiling is 15 times higher than what it was under the 50-50 scenario.
Having a large number of diverse messages hedges you against credibility bankruptcy. Combining that message inventory with even minimally-effective personalization puts you on track to not just keep your users, but actively engage them.
