1.2 A Closer Look: LuxeUnique
Phil started his menswear store in 2000, long before the mainstream acceptance of marketing analytics. His well-tailored suits are popular around the world, with consumers ordering them from right around the corner and abroad. Celebrities have worn his unique tuxedos on the red carpet—in fact, every time a famous artist appears in his clothes, orders skyrocket.
Like many entrepreneurs, Phil has followed his own vision. He designs his suits, tuxedos, and accessories for people like himself. “I never rely on focus groups or any of that,” Phil said in a recent interview with a fashion magazine. “I listen to my customers, and I follow my vision.”
June Reilly, his new vice president of marketing, would like to be more systematic in the use of analytics to increase Phil’s market share. “We have a strong, loyal customer base: people who have been buying your suits for years, who would never think to buy a special outfit anywhere else. But sales have been flat for the past two years. We need to attract new customers. To do that, we need to find out what every consumer of menswear wants, including those who are not buying from you now,” says June. “In addition, we need to measure the health of the business. How loyal are our customers? How engaged is our social media following? Are online sales the way to go, or do people prefer to shop in our stores? Knowing all of this will help us know how to grow our business.” “Go for it,” said Phil. “But how can you be sure you’re getting the full story? A survey can only tell you so much. And focus groups are just the opinions of a few people willing to get together and share their views. I’m not convinced that data will help us solve the problem of flat sales.”
June understands that Phil is skeptical. Data needs to be skillfully collected and interpreted wisely in order to be useful. If it’s collected carelessly, or interpreted without close analysis, it can mislead a business into making the wrong decisions. The key to using data for an initiative as comprehensive as growing Phil’s sales is to collect data that Phil and the team can trust. This means using a variety of data sources.
“We’ll look at a wide range of sources,” says June. “We won’t rely on just one. Collecting both qualitative data, like focus group feedback, and quantitative data, like projected sales trends in menswear, will give us a pretty full picture of what consumers want. We’ll be able to feel confident that the data we collect is thorough enough that we can base business decisions on it.” June crafts a program to collect a wide range of data, to guide LuxeUnique into a new era of sales growth:
The social media manager, Eddie, collects all the comments on the last two years of Facebook and Instagram posts. He uses a text analytics tool to measure the tone of the tweets on a scale from positive to neutral to negative. This is called sentiment analysis. It’s a form of qualitative data that shows how happy customers really are with a brand. He also hand codes this qualitative data to show trends, such as preferences for certain fabrics and colors.
He also uses a social media management and analytics tool to look at the reach of Phil’s social media messaging. He gathers data on the geographical areas where their social media posts get the most engagement. The tool also provides data on what posts get the most likes, retweets, and shares, and whether direct messages to Phil’s social media accounts are mostly positive in sentiment.
The e-commerce manager, Julie, looks at LuxeUnique’ website metrics. She looks at data on how many total visitors come to Phil’s website, how many visitors make a purchase, how they find the site online, and how long they spend browsing products online. June is very impressed that all of this data is available about the website.
The team further looks at metrics related to their cash register sales, online orders, and customer database. They determine how often a typical customer buys from Phil’s and the average value of orders received online versus the average sale in the store.
The team doesn’t stop, however, with digital marketing metrics alone. Though an important part of marketing analytics, the data generated by digital platforms are only part of a brand’s vital measures of success. The team also gathers critical qualitative data:
June sets up a focus group with area people who wear menswear suits and accessories. The participants are people who have never bought from the company before. She asks for their candid opinions on fabrics, styles, and prices. She asks what would encourage them to shop at Phil’s.
Her team conducts a survey of Phil’s current customers. In the customer survey, she asks the same questions as she does in the focus group, to compare customers’ answers with those of people who don’t currently shop at the stores. In addition, she includes Net Promoter Score (NPS) questions—a special type of customer survey question that asks whether customers would recommend a vendor to a friend. We’ll learn more about NPS in a later chapter. It’s important to June to ask NPS questions because high NPS scores are associated with company longevity. June wants to know about the overall health of the business, and since NPS is one metric of goodwill on the part of current customers, she considers it a critical metric for any business that seeks to grow.
The business operations team purchases an analyst report on sales growth and key trends in the men’s fashion industry. Analyst firms are companies that do independent research on specific industries. They gather both quantitative data, such as economic forecasts on the demand for a given product, and qualitative data, such as expert opinions on an industry. These reports are often valuable for their comprehensive scope and objectivity.
Figure 1.2 Analytics Activities in a Typical Week for a Business Marketer
“This data is really compelling,” says Julie. The data shows that Phil’s customers are loyal, recommending the brand enthusiastically to their friends. They care about trends, commenting actively on social media about their favorite fabrics, styles, and colors. The team can even see what types of suits get the most attention on social media.
When it comes to e-commerce, they learn from the data that customers find LuxeUnique by searching online, or via social media posts. But, they find, these online customers do not spend as much as shoppers in their stores. There is good news, however: in the past six months, though overall sales have been flat, online sales have grown by 30%. And most of these online sales come from new customers who found the brand on social media.
This data gives Julie many ideas for how to grow Phil’s sales. Maybe Eddie, the social media manager, should post more often to Instagram, given that social media posts have driven a lot of new sales. Asking loyal customers to share the company’s content with friends might help too. After all, almost all of the existing customers said they would recommend Phil’s to a friend. The analyst report says that practical fashions will see strong sales next year. Maybe it’s time to expand to a more practical fashion line, attracting new customers. And we know that customers are searching via Google and other search engines for such fashions, so it’s important for the company to be seen online. That means new ads, improvements to the website, and other ways of increasing the company’s online visibility. Collecting all of this data took time, but it has paid off in new ideas for business growth.
June presents all of this data to Phil. “Wow, this is truly useful data on what our customers like, what they do, how they feel about us, and their shopping behaviors. It will really help us keep their business. It’s also so good to see ideas for getting new customers that are based on credible data. Let’s try the strategies you developed. Because you based them on all this well-researched data, I feel confident in the ideas.”
June and the marketing team are excited to try their data-driven ideas. They will start creating more social media posts to drive sales, develop a new practical fashion line, and start a customer loyalty program that also incentivizes customers to recommend Phil’s to their friends, rewarding customers with $25 coupons for every referral they make. “I can’t wait to see the results of these initiatives,” says June. Thanks to her team’s new ability to use data, they will be able to measure these results more accurately than ever. “It’s a new, data-driven era for LuxeUnique. Here’s to using data to drive business growth.”