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How to tie customer data analytics to your bottom line for real ROI

Retail Writer

Retailers focus a great deal on customer data analytics because it solves one of the biggest conundrums in the business world: getting the right message to the right customer at the right time. It's important to emphasize "right" because that's what's usually missing from the marketing equation.

In the era of shrinking budgets, marketers must answer for every dollar spent. Return on investment (ROI) and customer experience are the two most important yardsticks chief marketers use to measure success. Fortunately, capturing and using customer data the right way can help increase ROI and improve customer experiences.

Data lights the way

The adage "the customer is king," has never been more relevant than it is now. Today's consumers decide what they want, how and when they want it and where they want it. Instead, it's imperative for you to understand exactly how they think and behave through.

Retail data is constantly telling us not only what has taken place, but also what is going to happen next. It offers helpful details into past interactions and preferences. Similarly, data patterns, which come from information collected over time, can help predict future behavior and retail insights. That's why, with the evolution of customer data and retail analytics, retail marketers are better equipped to improve customer experiences, build loyalty and increase conversions, all of which drive profit and ROI.

To take the right steps, you need to capture, store and utilize shopper marketing data to your advantage. Don't let it languish in databases!

Customer data analytics and the right strategy lead to improved ROI

To tie together data and ROI, retailers must build actionable strategies focused on using information to create compelling customer experiences. Say a retailer has data on what triggers an online shopper's conversion to purchase. How can the brand replicate that experience multiple times? How does it know when customers want passive or active brand interaction in the buying cycle?

By putting the right data strategies in place, retailers can create marketing programs that deliver. Here are three steps to reach this goal:

  1. https://kapost-files-prod.s3.amazonaws.com/uploads/direct/1442869261-16-8151/custdata_blog.jpgIdentify your ideal customer. It's common for businesses to have great and not-so-great customer relationships. You can pick out some of the great ones and compare, contrast and segregate their information in your database. You can even trace back information such as what inspired those customers to buy from you, what they like most about your brand and, of course, how their purchase patterns have changed. This allows you to gain a clearer picture of what your ideal customer might look like. With this model, you can identify those shoppers that behave like your high-value buyers — the ones with a significant demand for what you sell.
  2. Regularly cleanse your customer data analytics to keep them accurate, updated and actionable. The results of your data-driven actions depend largely on information quality. The challenge is that customer data keeps changing. According to a Dun & Bradstreet white paper, 62 percent of companies change their contact information within a year. Business phones are frequently disconnected, and C-suite members change. Company data must be streamlined or it becomes useless.
  3. Focus on marketing's new key performance indicators. Attracting more buyers is no longer the Holy Grail of marketing. Considering that replacing customers costs businesses six times more than retaining them, according to Forbes, it makes perfect sense to invest in satisfying current customers. This is why marketers must focus on fostering stronger, longer-term customer relationships. Similarly, one of marketing's responsibilities must be to turn employees, who are effectively the first customers, into brand advocates. When you build data strategies to reduce attrition and increase customer retention, you'll directly benefit your bottom line.

In the future, retailers will continue to use retail analytics more frequently to predict action. However, success will depend on how accurately they capture, interpret and understand data. This is a worthy investment if your business hopes to generate real ROI.

Connect with IBM data analytics professionals for a thorough retail analysis of your business.