Back-to-school is in full swing. And according to an infographic by Shoppertrak it looks like 2015 will be another impressive year for those who can take advantage of it.
- 80M Millennials are projected to spend 600B in 2015 collectively.
- Digitally-influenced purchases are projected to top 2.2T in 2015 (compared to 1.7T in 2014).
- 29% of households with school-age kids (6-17) plan to spend more than last year for back-to-school, compared with nearly 24% who said the same thing one year ago
Understanding why retail shoppers do what they do and how they want to engage to better influence where they’ll spend next has never been easier.
Why? Because busy consumers are leaving valuable digital footprints across each go-to platform and devices. Every instance of consumer engagement (every click, like, and x) can be turned into actionable insight for improving a retailer’s performance in near real-time.
But it hasn’t always been that easy—especially the ability of retailers to understand a single customer at such a finite level. Before digital data, consumers had a notion of what they wanted and made purchases when and where it felt right. Any insight retailers had into how people were buying/not buying was often after the fact, and conclusions drawn from buying/not buying habits could only send retailers in a general direction toward their revenue goals.
Today, organizations are equipped to “see” individual consumer activity as single digital points across the entirety buyer journey. This means retailers can leverage information at both a granular level (what shoes Wendy bought on Monday) and from a higher, more collective view (who else bought those same shoes and what do they have in common?).
Recommendation engines are increasingly being used in retail to make sense of and steer consumer activity in a company’s favor. And the tools/outcomes provided by these intelligent platforms are many depending on the given need. In particular, marketers are leveraging “trends” tools to capture and take action on trends among their own customers.
What does a typical trends tools look like?
Trends tools in general will use a stacked matrix to visually represent a retailer’s catalog. The matrix can be accessed by a marketer or other point person to get real time information on customer trends and is ordered in an intuitive way that can be “drilled into” at varying levels. For example, a matrix may include:
Categories (boys, girls, women, men)
Lines (boys shoes, boys shirts, boys pants)
Sizes (boys shoes size 8, boys shoes size 10)
Brands (Nike, Adidas, Underarmour)
How do marketers review and act on trend data?
Using trending tools, companies can see how they are doing compared to themselves at the retail level and take actionable steps towards business goals. Improving revenue, getting rid of out-of-season inventory and leveraging the popularity of one product to increase the selling-power of another are just several of many actionable steps retailers can take using data from a recommendation trend tool.
Take this scenario as an example.
A retailer carries several brands of boys skate shoes in their inventory. A team in marketing has been given the responsibility keep track of how each brand is selling (daily, weekly, monthly, any time period) in relationship to the other. This particular day, marketing notices one brand beginning to trend higher than the other. What strategic decisions can the organization take with respect to this information?
Actionable steps vary from one retailer to the next but certainly several options might be:
- Increase prices on that brand
- Promote that brand further
- Drop prices on other brands to make more room in their inventory for more successful brands
The Strands Retail Trends Tool allows you to quickly understand what’s selling like hotcakes and what’s losing steam across every category on your website. Find out how to leverage that information to promote the latest and greatest across all devices, a build the most enticing and personalized homepage imaginable.