Stalking Privacy

TargetedTHE ERA OF INDIVIDUAL PRIVACY may turn out to be a mere blip in the sequence of human history, as the smothering embrace of the World Wide Web makes our every click and consumption act a new molecule in the Big Data tsunami. Marketers salivate at the potential to sift the flow and aim relevant offers with pinpoint accuracy.

If they have their way unimpeded, privacy may turn out to be the human right that never was. People with means may put up barriers to make their personal information difficult to obtain. Everybody else would stand naked in the virtual town square, shielded only by the sheer numbers of their peers.

No wonder reasonable people worry that targeting may easily transmute into stalking when marketers apply automation to their process. The mechanisms and practices are not readily visible to normal citizens. I think this makes the reality both better and worse than it really seems.

This morning I offered this perspective on RetailWire.com as part of a discussion, Are Shoppers Entitled to Privacy While They Shop? This is a topic rife with assumptions that deserve to be challenged.

Here’s my take:

There is no natural right to privacy in the public domain. But protecting privacy may be the preferred practice for marketers and even governments.

If I enter a place of business (in-store or online), I should reasonably expect that my behaviors are open for observation.

But I’m not obligated to like or accept this. I can vote with my feet, clicks and dollars by preferentially visiting or patronizing establishments that adhere to a less creepy standard.

So I would propose that marketers make a habit of disclosure that is not buried on page 18 of the terms of use. Reminders about shopper tracking should be automatic and opt-out mechanisms provided.

If consumer privacy can be bypassed in the name of marketing relevancy, then certainly the marketers themselves should have zero expectation of privacy about their methods and objectives.

Disclose. Disclose. Disclose. Let shoppers tell you what they will accept; then market to meet that expectation.

[Tenser excerpt from Are Shoppers Entitled to Privacy While They Shop? discussion on RetailWire.com, Mar. 15, 2013.]
© Copyright 2013 James Tenser

In-Store Sensing Tops Online Metrics

I POSTED THE FOLLOWING commentary this morning on RetailWire.com as part of a discussion, Can Online Shopper Metrics Be Brought to Stores? I believe online innovation has influenced expectations in the bricks and mortar world. Now stores are poised to deliver sensing that online players can’t ever provide.

I must disclose a recent, prior influence. This post appears just a few days after I made a very informative visit to eTailWest in Palm Springs. Talking with vendors on the exhibit floor, I was struck by their degree of online-only thinking. Innovative analytics tools abounded, but bricks & mortar perspective was in relatively short supply. Since 90% of retail sales still take place in stores, some balance is in order.

Here’s my take:

Online metrics have certainly raised the bar, but in-store sensing will bring its own particular nuances—in some ways surpassing online practices.

The In-Store Implementation Network identifies five senses of in-store: Demand, Items, Messages, Employees and Shoppers. DIMES is part of this 2011 workshop. If you are in a rush, click forward to slide #22:

Tracking shopper movement within the physical store is only one element of the Shopper term of the equation, as I see it.

The present discussion drills deeper into shopper data alternatives—to consider whether tracking mobile phones is a better choice versus analyzing security video versus installing special-purpose video networks versus tracking transponders mounted on shopping carts. (Have we totally given up on electric eyes and grad students with clipboards?)

Further choices include: Do we analyze whole paths or stick to zones? Do we infer shopper demographics from video images? Do we mesh tracking data with POS transaction data?

However data is captured, appropriate analytics must be applied to extract managerially useful insights. The outputs must be timely and in a format that is accessible to decision-makers.

This is a lively sector for our business. With many competitors vying to be the industry standard, I can only offer some general advice:

#1 – Don’t assume comprehensive understanding of your shoppers based solely upon path tracking data
#2 – Never install more technology than is needed to achieve the desired objective
#3 – Expect best practice to change rapidly in this arena
#4 – Results will vary a lot based on channel of trade

[Tenser excerpt from “Can Online Shopper Metrics Be Brought to Stores?” discussion on RetailWire.com, Feb. 5, 2013.]
© Copyright 2013 James Tenser

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.)
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