The Incredible Dissolving Store

Shopper CentricI WAS ASKED RECENTLY to address a group of consumer products managers about the possible future of Category Management.

The request came at a time when I had been devoting serious thinking to several topics that at first seemed only tenuously related. Computer-generated ordering is one. Optimization of markdowns is another. The impact of social, mobile and local media is a third. Then there was this trendy concept — Big Data — that keeps getting lots of mentions, but seems to defy clear understanding.

So what was I to make of Category Management in a world where these disparate forces swirl? More importantly, what practical insights could I deliver to this audience of the best and brightest that CPG companies had on their brand and account teams? I probably couldn’t tell them much they didn’t already know. Maybe I could try to make their heads explode instead.

Thought Experiment
I challenged this audience with the following thought experiment: Try to visualize what life could be like for Category Management professionals in a world with vastly more information and a good deal less control.

The diagram accompanying this post identifies ten factors or sources of input that a Category Manager of the future might incorporate into planning decisions. Many are already familiar — optimization of assortment, price, promotion and markdowns are well-established techniques built into software suites like those from IBM DemandTec. Other vendors offer macro space planning solutions, automated replenishment, capacity planning, In-Store Implementation and competitive analytics. These factors all interact in a dizzying matrix. But wait! There’s more!

Now fold in the massive influence of social/mobile/local media and online shopping and search behaviors, which are manifest as Big Data. We are witness to the vanishing boundaries of the in-store environment, due to the advent of personal digital technology, changing consumer habits, omni-channel business models and the immense flows of unstructured and structured data that these are creating for Shopper Marketers. I call this The Incredible Dissolving Store.

Big Data postulates that we will soon be routinely mining these external data flows for relevant behavioral insights and applying those insights on a continuous basis to enable shopper success and sustain meaningful competitive advantage.

Mix Mastery
It’s kind of like the marketing mix management problem. Heck, in many ways it’s a core part of the marketing mix problem. Shopper success — and therefore, the success of our category and promotional plans — are influenced by all these factors. Simultaneously. Continuously.

The increasing intricacy of the merchandising decision process reflects the proliferation of intersecting, measurable and optimize-able factors within the store. All these new data-based influences mean the locus of power is rapidly leaving the store and distributing across your customers’ mobile devices. The shopper is always in the center — no matter where you go, there they are.

It becomes increasingly apparent that Category Management in the Incredible Dissolving Store will not be about solving the equation — it will be about tuning the system. New analytics tools make the keys to relevance more accessible and more automated than ever. The life cycle of your decisions, shorter than ever. The power resides in the network and in the hands of individual shoppers.

Category Management, like it or not, is rapidly shifting from an orderly, controlled, recursive, planning process with boundaries and well-defined metrics into a deliberately dis-orderly, multidimensional, broad, shape-shifting and organic process that incorporates planning, detection, response and continuous strategic reconsideration.

In the Incredible Dissolving Store, we need to get used to the kind of ongoing discomfort this implies and think very carefully about the metrics we use to define success. If we listen actively and shed our bias, the shoppers will tell us what those must be.

© Copyright 2012 James Tenser

Assortment – A ‘Matrix’ View

IN FAST-MOVING CONSUMER GOODS, the art and science of merchandising requires an informed balance of interrelated decision processes.

Microeconomics tells us that product sales rate will be related to price, albeit somewhat elastically. Space planning endeavors to allow sufficient quantities of each product to be stocked to meet shopper demand, without tying up excess capital. Assortment planning attempts to fit the most productive and satisfying mix of items into the space available. Inventory management balances the labor costs of replenishing shelves against in-stock levels.

There are other “levers” that figure into the process – from promotions, to new product introductions, to the depth and timing of markdowns, to the influence of competitors and even the weather. Taken collectively, these amount to a matrix of influencers on productivity and rates of sales.

For the retailer this comes down to the simultaneous management of customer engagement, assortment optimization, and pricing and profitability management. Or, as IBM DemandTec director of product management Carol Teng expressed in “A New Generation of Assortment Optimization,” a recent webinar hosted by PlanetRetail: “The right focus; the right product; the right price.”

[Learn more about IBM’s DemandTec solutions at its “Revolutionary Decisions” microsite.]

Teng shared five guiding principals for assortment optimization that are well worth summarizing here:

  1. Put the customer at the center.Make decisions based on actual customer demand, enabled by lowest level of data available. SKU proliferation adds costs for both retailers and manufacturers. Extreme choice does not necessarily drive more sales. Manufacturers face added costs due to forecasting and planning. Shoppers ultimately pay the cost for more unneeded variety.
  2. Don’t rationalize. Optimize. Keep key variety on the shelf, not just a simplified assortment that results from a “rank-and-cut” process. Use analytics to identify the weak-but-unique SKUs that are incremental and therefore important to keep. Identify products that are duplicative in the middle of the assortment curve, freeing up space to add truly incremental items.
  3. Localize. Average assortments yield average results. Store clustering enables assortments that are appropriately tailored to variations in consumer demand. Employ clustering tools that enable the right assortments to be derived based on demand variations across categories, banners and stores.
  4. Leverage available technology. This unlocks greater analytical potential. More sophisticated merchandising decisions are possible because computing power, customer intelligence, item intelligence, and connectivity are all on the increase. Mine available rich data sources: store, category, shopper and operational.
  5. Processs and organization changes are critical. Advisory functions currently in place support Category Management and vendor relations. In the near future, new advisory functions are needed with specific assortment optimization expertise at the cluster and banner level, based on insights about customer behaviors.

“We believe customer assortment truly is the next growth lever in retail,” Teng said. The building blocks for this capability begin with superior data sources, like POS and basket analysis; frequent shopper data on re-purchase and brand switching behavior; and shopper panels that reveal losses to competitors.

Assortment and other merchandising decisions are best made not in isolation, but in an inter-connected environment – a matrix, if you will. Ultimately assortment optimization will depend on an understanding of incremental demand and transferable demand. Practitioners must monitor these continuously as situations evolve. For each and every SKU and store cluster.

© Copyright 2012 James Tenser
(This article was commissioned by IBM, which is granted the right of republication. All other rights reserved.)

It’s All About Conversion

Download DOES YOUR MERCHANDISING WORK? Where do shoppers travel and pause within the store? How and when do they view and respond to items on display and in promotional locations? Do you have a mechanism in place to capture and act on this vital information?

Chances are, your e-retailing rivals are way ahead of you when it comes to sensing, capturing and analyzing shopper behaviors, product views and conversions. Like it or not, the informational and analytic norms of the online world are today redefining best practice for brick and mortar retailers.

That reality is evolving fast. With the advent of new video technology solutions that sense and analyze shopper behavior, merchants are gaining the ability to understand what shoppers are doing, in every store, every day. Practical in-store sensing is coming of age. Meaningful conversion analytics can be at your fingertips.

Download Familiar traffic-counting systems no longer meet analytic and operational needs of the brick and mortar retail industry. Retailers face competition from online stores and from each other, as convenience stores, big box stores, and even apparel stores and supermarkets diversify their merchandise to compete for a larger share of shopper wallets. In much the same way that e-tailers use online analytics to improve their conversion rates, brick and mortar retailers need empirical data to gain actionable in-store insights and make better merchandising decisions.

Commissioned by LightHausVCI and prepared by James Tenser, principal of VSN Strategies, The Conversion Advantage explores why actionable insights begin with capturing key metrics about shopper behavior: by store, by category, and by product. The white paper demonstrates how using Visual Customer Intelligence (VCI) systems delivers these key metrics by capturing data on customer movement, browsing behavior, engagement, and shopper demographics. It shows how these metrics help retailers increase conversion rates, optimize staffing levels, refine marketing plans, and create winning strategies. (Click either graphic to download.)

© Copyright 2012 James Tenser

Price Image in a Transparent World

ONE OF THE SIDE EFFECTS of the “showrooming” panic which seems to grip some of America’s big box retailers has been a flood of learned and not-so-learned opinions from learned and not-so-learned analysts and observers.

Showrooming anxiety emerged during the 2011 holiday selling season, when chains like Target and Best Buy were revealed as victims. Shoppers were inspecting and comparing merchandise in their stores, then using mobile apps to find and order the desired items at lower prices from places like Amazon.com and Buy.com. The story had a second surge in media coverage during April, when Best Buy reported soft sales and the departure of its CEO Brian Dunn. There are too many articles to count about this. How important is it, really?

The Pew Internet & American Life Project reported Jan. 30 that about one fourth of shoppers had used a smart phone at least once to check a price in a store during the last holiday period. The release did not specify which types of products were checked most. I’d bet a month of sales that the skew was heavily toward high-consideration purchases like TVs and major appliances.

Nielsen recently released findings that suggest there is indeed a significant variation in impact of mobile device use across retail channels. Nearly three fourths of respondents said they used a smartphone to check prices on a consumer electronic item, while more than half said they had scanned a code with their phone in a CE store. This behavior was much less prevalent in most other product categories – but not zero.

The New Transparency
Clearly there is much more we need to understand about this shopper behavior complex — not only about how shoppers are altering their habits around certain purchases, but also regarding what brands and retailers should do about it.

To that end, DemandTec, an IBM Company, is now sponsoring a RetailWire survey with specific focus on how retail practitioners think brick ‘n mortar retailers should combat showrooming.This is a worthy undertaking with potential to help surface superior thinking about the new era of price transparency:

We’ll interpret findings from this study here later this summer.

Absent investigations like these, showrooming may remain a buzzword excuse used by unimaginative retailers to explain away their mediocre performance in the face of increasing price transparency. It’s already a hot-button headline word for the herd of analysts and reporters who interpret consumer behavior based on instinct rather then empirical analysis.

I’m concerned that retailers who focus too narrowly on defeating showrooming are at risk of actually defeating their own shoppers. I propose an alternative: Focus on helping them get the best deal possible — from your bricks or clicks.

It could be that showrooming is not all bad, if we pay systematic attention. It could be just the reality check you need on your price image that could enable early corrective action.

Retailers collect slotting, display, and promotional allowances from manufacturers in exchange for putting products on their shelves. In some sectors, the net profits from these activities exceed the net profits from sale of goods. A lost sale, while unfortunate, is not a fatal occurrence. And manufacturers may still have powerful incentives to pay allowances to physical retailers who put their products on display — even if some resulting purchases take place online.

© Copyright 2012 James Tenser
(This article was commissioned by IBM which is granted the right of republication. All other rights reserved.)