Does Your Retail Data Answer the Five Ws?

Author: Kelsey Cervantes, Marketing Analyst

What would you say if I told you that your marketing and IT departments need to cozy on up together to achieve your goals? Two areas that were black and white in a traditional world are now gray and fuzzy in a digital one. Smart companies are harnessing the power of a modern data architecture (that’s right – Big Data) to gain insights into their customers’ ideas, behaviors, and actions.

Let me throw some numbers at you. Fifty-four percent of companies say their biggest challenge to data-driven marketing success is the lack of data quality and completeness. Seventy-eight percent of marketers believe the CMO should be the driver of a data-driven customer strategy, but only seven percent say they are able to deliver real-time, data-driven engagements across physical and digital touchpoints, and only five percent say they are able to determine the bottom-line impact of these engagements.

Why do you think so many companies are facing these issues? Because their marketing and IT departments haven’t teamed up to tackle data in a useful way. A modern data architecture has the solutions to your problems if you have the power to access and use it appropriately. So whether you’re a marketing or IT professional – or are just someone who wants to improve your business – read on. Does your current data really answer these questions?

Who are my customers, really?

According to the CMO Council, only six percent of marketers believe they are able to get a complete view of the customer from all available data sources. Yikes! That’s a scary statistic. Consumers today want brands to know their needs and offer them extremely valuable products and ideas. If you don’t know your customer, that’s simply impossible.

A modern data architecture has the answer for you: a 360° Customer View. Gain insights into your customers’ demographics, interests, behaviors, and more to understand who they truly are and how that affects their purchasing decisions at your store.

Let’s say you’re a shoe retailer, and you have two customers, Addison and Dennis. (Okay, you have thousands of other customers, but let’s focus on them.) You’ve collected the minimum amount of information needed from them to make a purchase at your store. Addison purchased two pairs of boots online with a credit card in a different name (but same billing and shipping addresses), and Dennis purchased one pair of tennis shoes in your store with a check. Addison subscribes to emails, and Dennis receives a monthly coupon at his home address.

With this limited information, what else can you know about these two people? A modern data architecture can connect these dots – and dots you don’t yet have – to form an understanding of these people and allow you to personalize their experiences more effectively.

Addison is a teenage girl, still living at home with her parents. She likes receiving your emails because she always wants the latest fashions. She’s a junior in high school and is very into pop culture. She plays volleyball and tennis, but she never buys athletic shoes from your store. There is not a brick-and-mortar location in her city, so she only shops online. Your emails to her should showcase the latest trends in fashion shoes (with celebrity icons if possible), deals on athletic shoes, and online exclusives.

Dennis is in his early 60’s and lives in a modest home with his wife. Their kids are grown, and Dennis now enjoys the simple life but is not yet retired. He owns a credit card but rarely uses it, and one of your brick-and-mortar locations is just a 10-minute drive from his house. Even though he receives your monthly mail coupons offering a wide variety of deals, he only comes in a couple times each year, and he buys his dress shoes elsewhere. Personalize his experience by sending him mail coupons that are more relevant to his purchasing behaviors, and start expanding from there by offering deals on your women’s shoes for his wife and raising his awareness of your dress shoe selection.

This information is out there; you just don’t have it yet. A modern data architecture can bring it to you.

What do my customers really think about my brand?

Most retailers are doing some form of social media listening already. But how much data are you gathering, and how do you measure it? Social media is a beast, and the data collected from it is extremely complex.

This is Big Data’s bread and butter. A modern data architecture can harness this data and turn it into actionable items for your business without the need for you to spend hours scouring social media, and then spend several more hours trying to make sense of the data storm you’ve collected.

It’s important to remember that knowing what your customers think about your brand isn’t just a superficial marketing idea. It’s the core of your business. If what you’re putting down is twisted and misunderstood by the time people pick it up, that’s a problem you can recognize and take steps  to fix with the proper data. If people are unhappy with a certain store location, that’s an issue you can look into effectively. If consumers in a certain area are looking for better selections of shoes, you may have found a new market.

Use this Sentiment Analysis to take advantage of the raw emotions and thoughts that consumers are offering freely on social media to better your business.

Where else are my customers shopping?

One of the biggest advantages of capturing information in a modern data architecture is getting to understand how your customers interact with your competitors. While you, of course, cannot access your competition’s internal data, there is plenty of public data floating around that you simply cannot harness without Big Data.

By understanding where else your customers are shopping, what they might be purchasing there, how much they’re spending, what deals they’re getting, etc., you can offer superior and more personalized solutions to your customers.

If Addison is buying her athletic shoes at only brick-and-mortar retailers, it might be because she wants to try them on before purchasing. Let her know she can exchange online orders at no cost to reassure her that she can get what she needs. If Dennis buys his dress shoes at the same store as his dress clothes, let him know that you can offer him better deals and a wider selection since shoes are your specialty.

When will my customers make their next purchase?

Okay, so a modern data architecture can’t predict the future with 100% accuracy. But as I hope you’ve gleaned, it can predict trends like no other. By accessing this vast data resource and understanding your customers better as the humans they are – rather than the sales they are – Big Data can help you influence their purchasing trends and trends of the general public as well.

For example, in mid to late November of 2017, there was a huge spike in shoe sale interest. Was it people preparing for snow and cold weather? Was it people shopping for holiday gifts? Was it people buying for themselves and taking advantage of Black Friday deals? Was it something else entirely? Knowing these trends – both on public and personal customer levels – will allow you to understand the best times to offer certain deals to certain customers.

Why do my customers leave?

There are so many reasons a customer might leave your store. Addison’s online order took a week longer to arrive than expected, and customer service was rude to her when she called to inquire. Dennis’s favorite sneakers are out of stock, and he doesn’t realize you offer a comparable product – not to mention other shoe lines that might interest him.

Whether it’s your pricing, your customer service, your website interface, your brick-and-mortar check-out process, your product offering, or what have you, a modern data architecture can help you understand why your customers are going somewhere else. Not only can it provide you with the trends that occur leading up to a customer’s final purchase (and what might happen afterward, like a poor customer service call, for instance), it can also help you identify the customers whom you might be on the brink of losing. Better yet, you can stay ahead of the curve and make sure you aren’t doing those things that cause a consumer to leave for your competition.

Bonus: How can I tell what else my customers want?

Market Basket Analysis is something many – if not all – of us have experienced while shopping. We just may not have known what it was at the time. Big Data here allows you to see what trends are happening when customers purchase certain products. For example, are people buying a certain kind of sock when they purchase a certain type of shoe? Are they more likely to buy other accessories when they buy more than one pair of shoes or are using a particular coupon or deal?

Knowing the answers to these questions can help you encourage customers to purchase more of the products they need at your store; they may just not realize it on their own. In a brick-and-mortar setting, you might offer a coupon on the shelf that says, “Buy two pairs of heels and get 20% off all hosiery,” or, “Get a $5 gift card when you purchase three pairs of children’s shoes.” Online, you might offer up some suggestions for what others purchase when they purchase a certain item or what items might go together well. In this case, you can display the combined price of those products with a button that can add all of them to your customer’s cart in one swift click. Easy!

—

Whew, who knew there were so many practical business applications for something as data-heavy as the modern data architecture? As you can see, these items aren’t things one department can successfully tackle alone. Marketing, IT, and other departments in your business should work together to accomplish these goals and understand how you can better serve Addison, Dennis, and all of your other customers, too.

It may sound like a lot to take on, and I won’t lie to you, it certainly can be. Luckily, the experts at Zirous can help your team set up the architecture and systems needed to access and actionably use modern, complex data to better your retail business and provide you with the needed support to maintain and understand your beautiful new modern data architecture. Contact us for a no-obligation conversation about how you can use Big Data to help your business.