In his book ‘The Power of Habit’, writer Charles Duhigg has explored how US supermarket Target can predict, with remarkable accuracy, when female customers are in the early stages of pregnancy.

How do they do it? With data.

Like many retailers, Target has built a sophisticated data analysis system to monitor customers and offer them personalised incentives to drive sales. By tracking her purchases, Target can not only ascertain when a woman is due to give birth, but can also guess her baby’s expected gender with 87% accuracy.

In our current society, data is the new currency. Some of the world’s largest businesses are built on it: Facebook and Google offer free services simply because of the value of your personal information for advertising purposes. For these reasons and more, data presents an ethical conundrum for people working in tech, including ourselves: One person’s convenience is another person’s infringement of privacy, after all.

At Calvium, we care deeply about the ethical issues surrounding customer data and privacy, and have explored these at length regarding digital placemaking, here.

It’s our job to carefully consider how data is used. Apps are an exceptionally rich source of customer information which, when analysed, can help optimise app software almost beyond recognition, crafting a better user experience and – in turn – greater ROI.

So long as users are informed about how their data is used, this data can offer a win/win for everyone involved – users, app developers and businesses themselves. Here’s what you need to know about app analytics.

Starting with ‘Why’

The sheer number of sensors and input devices on a modern smartphone or tablet means apps are capable of gathering a remarkable range of different types of user data. Much of this data will be of limited use to the organisation behind the app, however.

Instead, an effective data strategy for an app starts with knowing what you want your app to achieve, and therefore which data to gather to assess the success of the app. Different app; different data strategy.

ROI is the metric of choice for many marketing and business operations, but not always with apps. That’s because not all apps foster or encourage a purchase or a point of conversion – interactions that constitute a classic ‘Return on Investment’.

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An app designed to track water meter readings, for example, might be intended to drive brand loyalty by making it easy for customers to submit meter readings to their supplier. In this case, ROI is an inappropriate metric.

Here and elsewhere, we’d instead advocate tracking ‘Return on Objectives’, or ROO, which in this case might be enquiries made to the water supplier directly from the app.

When tracking ROO, the metric must reflect the objective. Many of the apps we build for enterprise organisations, for example, are designed to make processes simpler and more efficient. These include apps used to operate and monitor heavy, complex machinery. In these cases, the appropriate metric might be the volume of tasks handled by the app over a set period.

These metrics should be set against goals – expressed as KPIs – as early as possible following the launch of the app, then used to direct how the app is improved over time.

What else?

KPI-focused metrics make it possible to track the success of an app in meeting the investment made in it. But that’s not all analytics data can do:

Analytics for interaction

By uncovering how customers are acting, apps can show businesses how to interact with them.

Any app that includes a catalogue of products – like the one we built for Yachting Pages, for example – will offer rich data on the products and services that interest customers the most at different times, which retailers can use to tailor their product offering and how products are offered in the app, to drive sales.

Analytics for improvement

Any app used to facilitate learning a new process or new information will provide data on how to improve that learning process.

The app we built for the Háblame Bebé project, for instance, is designed to help Hispanic mothers teach their children the Spanish language. By understanding which pages and functions are used most in the app, the Háblame Bebé team can improve their wider language tuition methods, because they know which types of tuition their audience respond to best.

The same applies for apps designed to facilitate any process. Many of the apps we build for the Rolls-Royce group, for example, are designed to help expert teams operate mechanical systems. Tracking user interventions in the apps – and therefore in the corresponding mechanical systems – provides Rolls-Royce teams with rich data for improving their wider systems and processes.

Analytics for marketing

Of course, apps are also a rich fount of data for marketers because, very simply, they demonstrate which parts of a product or service elicit the richest response.

Heritage organisations including Historic Royal Palaces and Tower Bridge can use the apps we built them to track where users, or visitors, spend the most time; which areas they pass through, and even which parts of their exhibitions aroused frustration or confusion. This data can then be used to improve their wider visitor experience and focus their marketing messages in future.

Understanding user data and the insight it can generate is essential for any organisation with an app. User data can point to ways organisations can improve their user experience. By continuously learning from and improving their app, they improve their response to the original business problem that encouraged them to build an app in the first place.

For heritage apps, the data can reveal how and where people interact with its functionality, what they’re engaged with and what they’re not. For enterprise apps, the analytics can give detailed analysis of how workers tackle problems, where they struggle, and how long certain tasks take.

For e-commerce, businesses can see where they’re losing customers during the purchase decision, and test ways to convert more. For directories, businesses can monitor stock, see what items are regularly purchased with others and much, much more.

In these ways, and many others, data analytics have a compounding effect on the success of your investment in an app project. And sometimes, you might just learn more about your customers than they know about themselves.

In baking data strategy into our consultative, co-collaborative design approach, Calvium crafts app solutions that balance exceptional user experiences with invaluable data learning. Find out how our focus on optimisation has helped organisations across the heritage, engineering, architecture and logistics sectors in our case studies.