3 Ways to Turn Data Into Real Marketing Insights

Is data really making your job easier?

Anyone working in marketing or advertising hears the same things over and over: Data is ushering in a new age. Data is the key to knowing your customer. Data is redefining marketing.

But research shows a different story. Earlier this year, the CMO Council found that only seven percent of marketers are able to deliver data-driven engagements in real-time across physical and digital touchpoints, Even fewer—only five percent—can measure the impact these engagements have on revenue.

Finding consumers in digital and physical space, engaging them, then determining marketing effectiveness—aren’t these table stakes for modern marketing? Again, the research says otherwise: Experian found 92 percent of marketing industry professionals surveyed don’t have a single view of the customer. And a recent Forbes Insights study found that while nearly 60 percent of those surveyed believe analytics are vital to marketing success, only 35 percent say they have the analytics they need to inform their strategy.

If you’re a marketer struggling to reconcile data across channels, finding it a challenge to measure marketing effectiveness or despairing at lack of customer visibility, you are clearly not alone. But it’s time to change the statistics. Data is a tool that can unlock great opportunities for marketers, but it certainly makes it easier if you know where and how to apply it. Let’s talk about three ways to turn data into real, solid insights for better marketing.

Have a single view of the customer

You likely have many of the components you need to create a single view of the customer. Digital touchpoints, including email, social media and website, make up a huge portion of the modern marketer’s insight into customer activity. But the whole idea of this single view is to incorporate every touchpoint, including physical brand interactions.

There are a few practical things you can do to better create this continuity. On the digital front, associate your customers’ social login with their accounts by allowing them to register using their Facebook, Twitter or Google information. Many companies use this as a shortcut to associating their own internal data with a world of helpful, insightful external data.

On the physical front, associate transaction data with all other marketing data—your single view of the customer has to include in-store purchases and in-store returns in addition to online purchases, website visits, advertising clicks and conversions, social data and more. Transactional data will help you figure out how digital touchpoints are impacting purchasing decisions. You can even go a step further and add beacons to brick and mortar locations, associating store visits with customer profiles even when they don’t purchase anything.

This holistic view of customer-brand interactions will allow you to weight touchpoints, determine attribution beyond last-touch and more effectively optimize interactions across channels.

Turn touchpoint data into personalization

Once you have this data, that last point becomes possible—optimizing touchpoints in today’s world means personalization. Brands have been personalizing via segmentation for years, but with the amount of data you’re collecting about customers, you can individualize messaging.

You likely already have segments based on purchase history and store visits, or location and age. But with a single view of your customer, you should know the location, age, preferred social channels, frequency of store visits, purchase categories and more for each customer.

Combining those details allows you to send each customer the right message to prompt conversion. The new shopper who likes Instagram posts, has visited the page for a silk blouse four times but not purchased and doesn’t live near a physical location should get an Instagram ad promising a discount for their email address.

The shopper who lives in a temperate climate, buys at full price frequently and doesn’t use social media should receive an email showing how to dress in fall fashions despite warmer temperatures.

The difference in these two shoppers is huge. One is likely to buy given a little inspiration, and nothing more; the other needs a little prompting to make their first or second purchase, and while you’re at it, you’re gathering more information so you can stay connected and create brand loyalty.

Create personalized recommendations

These same concepts easily transition to recommendation engines. While many businesses have created them, they often poorly mimic some kind of category game: looks like you’re viewing a necklace, which is “jewelry,” would you like to see another “jewelry”?

The data you’re collecting for a single customer view and personalized messaging will carry over to recommendations easily. By tying transaction data to the customer profile, you can make sure to avoid recommending products the customer has already purchased. Additionally, you can create a recommendation algorithm trained on customer purchase history; if the engine has real customer data to process, it can do more than recognize and recommend simple categories or products.

With time, machine learning algorithms—which power recommendation engines—can get better and smarter. A continuous stream of customer data will improve your customer experience and what we all care about at the end of the day: your sales.

Make data work for you

Data can truly change the marketer’s daily life and make your job easier, but only when there are practical, realistic ways to use it. Starting with customer journey analytics ensures you not only have a single view of the journey, but can also personalize content and create brand loyalty. For more on customer analytics, check out the Forrest Wave: Customer Analytics Service Providers, where Clarity Insights was named a leader.