Retailers getting excited about data-driven marketing is nothing new.
What is unusual about Sears is combining data analytics and digital marketing into one function, headed by one person, and entrusting that role to an analytics guy – albeit someone who learned their trade at Google, Macy’s and Yahoo.
Kerem Tomak, Chief Digital Marketing & Analytics Officer at Sears and Kmart, shared the retailers’ and his philosophy and strategy with ClickZ at Modern Marketing Summit at Mobile World Congress 2017:
“I run digital marketing as well as analytics for Sears. I have been preaching the importance of the marriage of these two for a while.
“I came from a pure analytics background – from a world of manipulating data, to making sense of the data, to owing a P&L and running a marketing team that is tasked with growing incremental dollars for the business. This is a transformation for data analytics.”
Tying data analytics to business
To be worthwhile, data analytics needs to be closely tied not just to marketing, but also to all the business functions, believes Tomak.
“Data for the sake of data is pointless. The purpose of marketing analytics is to ask: what are you going to do with all this data to help the business?
“You cannot succeed in analytics and marketing unless they are central to business operations and are helping business answer the questions that will drive dollars to the top or bottom line.
“The more removed from the dollar impact analytics function is, the more irrelevant it becomes.”
Reacting to mobile location signals
Mobile is critical to this because it allows retailers to capture the signals – by analyzing customer’s digital behavior – that deliver insight into demand for products and services, existing and potential.
So what questions should analytics be answering for the business?
“The business questions are:
“How can we serve the customer better?
“What are they looking for?
“What are they asking for the brand to do?
“And what are the competitors doing that we need to do?
“It is the job of the analytics leader to answer those questions, because no one outside analytics knows what analytics is capable of.”
This is particularly important with mobile location data:
“With mobile location data, it is doubly important to reduce this distance between analytics and business, because you need react in near real-time to the signals from the location data.
“Analytics needs to be closely embedded and driving business. You need to minimize the latency between the customer action e.g. clicking on a search ad and the data being actioned.
“We call this closed loop optimization:
- The data is created, and captured, by a customer action.
- The analytics interprets that data and turns it into insights.
- The insights drive marketing.
- The marketing activity leads to a customer response, which creates data, which completes the loop.
“We are getting close to this goal with mobile location data. We know when a customer is near a store and what products they are looking for; if we know what products are available in the nearby store, we can point them in that direction using ads, search ads and messaging through our various apps.”
The Holy Grail: shifting excess inventory
Using location-based marketing and analytics to drive sales of excess inventory is more easily said than done.
“This is the Holy Grail in all of retail. But I do not know of anyone that has successfully connected marketing to merchandising continuously and at scale, especially big box retailers.
“The problem is that store data tends to be separate silos [each store has its own merchandising database]. The question is: how do you connect the stores with hundreds of thousands of products each in a central location with all of the customer demand data that comes in from marketing. It is a really hard problem to solve.
The problem is compounded by errors that occur with the way that merchandising data is compiled.
“It’s not just a problem of legacy systems; it could also be that the data itself is dirty. The problem arises largely because data is entered manually into merchandising systems so the same Calvin Klein product, for example, could be entered in several different formats e.g. Calvin-Klein; Calvin/Klein; CalvinKlein and Calvin Klein.
“If you don’t have consistent data that can be scaled and captured and recorded in the right way, then all of the analytics will be mute – you will have half-baked or even wrong insights that won’t drive business at all. It is: garbage in, garbage out.
“Data is still the barrier to doing things that are impactful or scalable. This includes location data. Location data is only useful if you can tie that to clean product information. This is still one of the biggest problems that we have.”
Today Sears and Kmart rely on third parties such as Google to target people who are searching while near a Kmart/Sears location.
The following screenshots were taken using the Mobilizer tool, showing products available in-store near Austin Texas.
“We are using local inventory ads from Google. When a consumer searches for a product on a phone or desktop, within 10 miles of a store, it triggers an image based ad in the search results for a products. On – or near – the product or on the image it says “in store” – this is the future of search as we see it.
“You click on the ad and it takes you to a landing page which shows a map with the location of the store, the price and availability of the product and opening hours and so on. So you can choose to go to the store and buy it – if they are searching on a mobile phone and have purchase intent they will purchase instore.
“This comes close to connecting the marketing and merchandising disparate worlds.”
For more on Mobile World Congress, read our previous coverage:
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