Missed the data boat? 3 ways to recover your mobile strategy

How to get your mobile strategy back on track

Next-generation mobile strategies depend on having a solid data strategy. Consumers have little tolerance for generic content that doesn’t speak directly to their interests, so most Fortune 500 companies have shifted toward customized experiences. Good user experiences revolve around effective personalization, and you need high-quality customer intelligence in order to provide that.

Data allows you to better understand your customers, and smart data builds trust. Traditional tools such as geofencing and wireless access points, among other technologies, create a picture of people’s behaviors so you can sell to them according to their circumstances. Modern marketing strategies are adaptive, shifting as they gather more details about audiences.

The way you market to someone browsing your app at home is different from how you’d approach them in your physical store. You might entice them to the shop with a coupon generated through the app and then send more specific offers based on where they are within the physical space. Once they leave, you need to re-engage them digitally so they’ll come back or recommend your shop to a friend.

Experience is at the core of these next-generation mobile strategies. But building an experience is different from building an app or a website because it must be contextual and relevant, unlike most websites and mobile apps. Data helps you compile profiles as soon as first contact is made, rather than prompting customers to fill out lengthy online questionnaires. Then you can design a simple, inviting onboarding process. This persuasive strategy builds on itself, drawing users back to your brand again and again as you provide increased options. The more often people use your mobile service, the more data you have to improve the experience.

Playing Catchup in the Data Age

But what happens to companies that don’t have robust data-gathering mechanisms in place? If you missed the era of unifying and aggregating your data, you’re probably relying on legacy IT and software paradigms. You will face challenges to personalization because legacy systems have struggled to implement new data-based infrastructures. They’ve created plug-ins to connect with new technologies, but scaling costs are extremely high, and the systems are like patchwork.

In the past, IT infrastructures weren’t built for aggregating hourly input from smartphone and environmental sensors. Engineers didn’t construct platforms with the intention of combining users’ Facebook and banking data, and they hadn’t yet heard the phrase “Internet of Things.”

But talk to any chief digital officer or chief marketing officer today, and they’ll tell you that such data integration is mandatory. They want to know that when one of their company’s Facebook fans walks into their store, that person will automatically receive a promotional offer. To enable that function, they need to pull data from a variety of interconnected sources. Digital officers have great ideas and use cases, but are often slowed down by IT.

If you’ve fallen behind in data aggregation and personalization, there’s still time to regain ground. Start by introducing one protocol or unifier around which you can build a campaign. Social media platforms such as Facebook, Twitter, and LinkedIn provide a wealth of consumer data that you can parse for personal information. Don't forget: You need to maintain the trust of your customers along the way. Use relevant techniques like encryption and tokenization to protect their privacy.

People often share their locations and what they’re buying with their social networks, so start here while you build out a better aggregation platform. Launch a hashtag campaign in which everyone who tweets using the phrase while shopping in-store gets a discount code. That’s a great mobile marketing opportunity.

Implementing a Next-Generation Mobile Strategy

Ultimately, you need to create a comprehensive, one-stop-shop for data aggregation. Your competitive edge depends on your ability to connect meaningfully with customers. Here’s how to achieve that:

1. Organize small, autonomous teams to focus on personalization.

Task a small, agile team with your personalization initiatives. I like to say that you should be able to feed your teams with a large pizza; any more people than that, and you risk a “too many cooks in the kitchen” scenario. Bring together a developer, UX designer, business analyst, and marketers who have complementary skill sets. Then, give them the autonomy to develop a data solution that fuels your campaigns.

The integrated team approach allows you to launch new strategies quickly. When you take a hierarchical tactic, every aspect needs to cycle through marketing, IT, and your business analytics units individually so everyone can sign off on the KPIs. This can take months or years to complete. Interdepartmental collaboration is much more likely to produce fast, successful results. And time is of the essence for personalization.

2. Overcome IT infrastructure hurdles.

Refocus your IT efforts around data unification and building a context hub for your company. You want a user-friendly interface on both the front and back ends so staff can enact new strategies and your audience can easily navigate your app and site. The new system should serve as a data aggregation hub for gathering actionable insights about your audience.

Having an intuitive user interface will encourage people to use your app or website regularly, which will generate more useful data. This leads to better personalization and allows you to push more relevant promotions when people come into your store.

An IT overhaul can boost every aspect of your user experience. Consider the U.K. fashion brand Oasis, which integrates tech into every customer touchpoint. Retail associates carry iPads so when customers are looking for items in the store, someone is available to help them find it quickly. The iPads double as checkout counters, and associates can look up customer data and place orders on their behalf. This is the type of personalized, on-demand service that consumers expect.

3. Market on the basis of user context, not just location or persona.

Use the data you collect to deploy omnichannel strategies. Your system should adapt according to whether customers reach you via desktop browsers, smartphone apps, or wearables. Context-based marketing is the height of personalization. People demand messages that are applicable to their immediate circumstances.

Because people enter their stores for different reasons, Walmart approaches personalization differently from Nordstrom. A Walmart customer likely writes out her shopping list ahead of time and wants to move quickly through the store. Walmart needs to make it easy for her to achieve that goal.

When people visit Nordstrom, they want a luxury experience. They’ll take their time trying on clothes and browsing jewelry, and they have more of an appetite for reading extensive information on their mobile phones. Walmart and Nordstrom send alerts and promotions based on the context of why people visit their stores.

A few years ago, data and personalization gave retailers a competitive edge. Now, they’re lifelines for companies that haven’t yet caught up to the digital age. If you haven’t implemented a data unification strategy, that’s where you need to focus your energy. Your customers are waiting for you to deliver relevant, customized content when and where they want it.

Dr. Hossein Rahnama is a recognized figure in ubiquitous and pervasive computing and the founder and chief product officer of Flybits, the context-as-a-service company. His research explores artificial intelligence, mobile human-computer interaction, and the effective design of contextual services. Hossein has 30 publications and 10 patents in ubiquitous computing, and is a council member of the National Science and Engineering Research Council of Canada (NSERC). Hossein is also a visiting scholar at the Human Dynamics group at MIT Media Lab in Cambridge, Mass. He has a doctorate in computer science from Ryerson University.