Why These Three Retail Marketing Measurables Matter

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Why These Three Retail Marketing Measurables Matter

By Venkat Viswanathan, Founder, LatentView Analytics - 09/01/2015
Demand in the apparel industry is largely determined by fast changing consumer tastes and preferences. With millennials emerging as the largest consumer group in the U.S., apparel retailers have already felt the challenge of being relevant to this group.

Teen clothing brands experienced dips in sales in 2014 in the critical back-to-school season, and retailers are hoping for better revenues this year. As the largest peak shopping season second only to the winter holidays, the July through September period, dominated by school-related apparel and other products, represents a huge opportunity for retailers to capitalize on foot traffic, maintain or enhance loyalty with consumers, and strengthen their relationships with millennials.

But it's not easy to earn dollars from millennials or their parents. One recent report by America's Research Group found that 58 percent of parents surveyed reported they would spend sparingly during the back-to-school season, preferring to wait for deals that may come later in the fall, during Thanksgiving.

The season is also known for being extremely competitive and promotional as retailers look for every opportunity to draw consumers in. But marketing programs can't be a one-size-fits-all approach; the trend toward personalization in shopping also applies to marketing products to the shoppers they want to reach.

Retailers and apparel brands must battle for those dollars using their best asset: data. And the volume and veracity of that data is growing. A recent report by analyst firm IDC found that in 2013, only 22 percent of the information in the digital universe would be available for analysis. That is, enough was known about the data to characterize it to make it worthy of analyzing for insights. By 2020, the useful percentage of data could grow to more than 35 percent, according to IDC. Such exponential growth means a significant competitive advantage for those businesses that process and analyze their data from sources including website traffic, mobile devices, social media, and geospatial and historical data on consumers.

Here they are: three key measurables
Retail has considerably smaller margins than other consumer-focused businesses, making the need to match demand to merchandise, capture opportunities, minimize error and optimize for maximum revenue an even greater priority.

Retailers can use marketing analytics in order to:

Identify emerging trends and preferences: Digital data can provide retailers with deep insights into emerging clothing trends, preferences for colors, material and designs. Retailers can predict when a specific fashion trend is going to gain critical mass, or when it's time to phase out a particular line of clothing. Abercrombie & Fitch recently took a $27 million write-off to get rid of old inventory and become more relevant. Data can help retailers stay ahead of the curve, or at least with it.

Refine sizing and optimize inventory management: Nobody likes it when they find that perfect piece of clothing but it's not available in their size, especially millennials, who gotta have it now — right now. Digital data in combination with internal data like transactional history, CRM databases, and customer support logs can provide powerful information that can predict not just what sizes should be stocked but also what designs, colors and material are more likely to sell in a specific retail outlet. There is a huge variation from region to region and even neighborhood to neighborhood.

Increase brand engagement: Digital marketers have realized the importance of engagement over volume of likes. But they still struggle with measuring how engagement is impacting business. Being able to capture large quantities of data from various sources in a timely manner and presenting it in a way that can be easily understood by senior decision-makers is essential to this category. Digital marketing dashboards not only can help understand how campaigns are performing or what sentiments about a brand or product are, but also map that performance against real business indicators such as sales or category growth.

Align marketing analytics with business priorities
Is your retail enterprise already tracking those three measuables? Marketing analytics is being applied in retail with these goals in mind, and while they seem obvious, achieving these and other objectives remains elusive to many retailers. One of the reasons that digital marketing is less than successful in meeting these objectives is that decision makers in the retail and apparel industry aren't asking the right business questions, and they then analyze data based on those questions. These questions cover a wide range of issues or challenges: how do we attract millennials? How can we drive customer loyalty? Where are our customers coming from? How can we further customize our marketing programs?

In the apparel industry, many of these questions will revolve around seasonal data; for instance, marketing analytics can help retailers determine when business cycles will slow down, when to shift spending from one marketing channel to another, and when certain products are most popular and should be made more available to consumers.

For many retailers, marketing analytics can help make the critical back-to-school season a success by focusing on the three key measurables above in greater detail. Just as many consumers are predicted to be flexible with how they spend money during this shopping season, marketing analytics in turn gives retailers the ability to become flexible with how, when and where products are marketed.

Retailers can capitalize on these business objectives with the combination of a marketing analytics platform along with broader readiness that includes support from management, access to quality data and a balance of long-term and short-term expectations for results.


Venkat Viswanathan is founder and chairman of LatentView Analytics.