Mobile engagement is great, but engaging with mobile isn’t enough. More people tapping on push notifications or opening your app is awesome, but it’s a means to an end. The real proof that mobile pays off comes from closing the loop; tracking a sale from initial touch to completed sale.
Tracking customer journeys directly connects marketing activity to sales
By following a customer’s journey from the first interaction right through to sale, you can see which promotions and channels lead to them buying something. Did Steve come in-store on the back of a limited time offer or to claim a reward? Was it price promotion or a gift with purchase? Did he cross a geofence, or set off a store beacon? Did he see a push message or did he click on the offer inside your brand’s app? What exactly was it that resulted in him handing over his cash?
You can report on in-store sales and mobile promotions separately but without closing the loop at the point of sale you can’t know the exact relationship between the two; which bits of your marketing mix have a material impact on sales and thereby revenue. And that’s the information that turns marketing from indirect expense to a direct cost of sale.
Closed loop analytics does what it says on the box: closing the loop by analyzing how in-store purchase connects to mobile activity.
Marketing automation is a good start – but don’t stop at counting clicks
The good news is that some form of marketing automation will get you most of the way to making this happen. After all, email automation software has been tracking opens and clicks for years, and most mobile solutions are just as good at reporting interactions - the essence of descriptive analytics. But you don't get much out of simply measuring interactions with your marketing campaigns – you don’t just want to know someone’s opened your email. If that’s as far as you want to take the relationship you could just request a read receipt (good luck with that!)
If you've gone so far as to set up email automation (most likely with a CRM behind it), what you really want to know is which emails - what subjects, content, outbound links, time and day you sent them – lands you a customer or helps you sell more to an existing customer. The same applies to mobile marketing: in the end it comes down to making that sale – and the next one, and the one after that.
Transaction data on its own – and we know everyone has a lot of it - isn’t enough either. While it’s good to know Amy is buying more often, if we can’t state exactly how marketing made that happen, we can’t claim responsibility for the win (or the next one).
Closing the loop and removing friction at the point of sale
So beyond engagement, and beyond automation, you need some analytical capability that will not only link promotional campaigns and mobile activity to sales, but tell you which combination will net you further sales. By identifying patterns of customer behavior you can predict which content is most likely to convert for each, and target the right offers to the right people at the right time.
Granularity depends on your customer segments and marketing needs, but we believe you should use location and other live data to personalize at an individual level. Then as you add more data to your model, your ability to predict behavior is improved, and your marketing becomes even more laser-focused.
And because this is mobile personalization, why wouldn’t you include live data in your model? The more of that you have, the further you are down the path to hyper-personalization: you know to send Tim an up-size offer as he’s leaving home on a Monday morning, Dan a limited time promo when he’s in town on Wednesday afternoon and Aaron a sweetener when he’s spent a good 15 minutes in-store deciding between two items.
The ultimate aim should be each customer seeing exactly what they need to in order to convert without thinking too much about it. Which (assuming you’re not causing them to look around for hidden cameras) can only be a good thing…