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.

Smartphone by Store Nielsen recently released findings that suggest there is indeed a significant variationin 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.)

Lessons from the Transit of Venus

YESTERDAY I ATTENDED an event that will never be repeated in your or my lifetime. It was a viewing of the transit of the planet Venus across the face of the sun. That’s something like a solar eclipse by the moon, except much rarer and quite a bit harder to observe since Venus is much farther away.

The kind folks at the Loews Ventana Canyon Resort here in Tucson hosted the afternoon on the hotel patio, and scientists from The Planetary Science Institute, also based here, were our very enthusiastic guides. They set up several specialized solar telescopes for public viewing and presented a series of lectures which explained what was happening and what it meant, astronomically speaking.

The story of the transit of Venus is as much about cultural history as it is about science. For many centuries, natural scientists have been aware of the relative movement of the sun, moon and planets. Venus is the most visible object in the night sky, after the moon itself, but it is not normally visible in the day time. The transit itself happens in pairs, eight years apart; pairs then follow alternately by spans of 121½ years and 105½years. This makes it nearly impossible for a single observer to study.

According to the PSI scientists, it took several centuries for European astronomers, working in concert, to recognize and work out the basic facts of the transit. Once they did get it figured, it yielded important insights about such matters as the distance and size of the sun and whether more distant stars might also have planetary systems.

With the special telescopes it was easy to for us guests to observe the dark dot of Venus as it crept slowly across the solar disk. Several sunspots and solar prominences were a fascinating bonus. The lecturers had tons of anecdotes and insights about what could be learned from observing and measuring the transit.

Since I tend to view our world (and other worlds!) through the peculiar lens of the retail marketer, I was bound to consider what lessons we might derive from the transit of Venus. Several learnings came to mind:

You can see a lot just by looking.* The transit of Venus is hard to view due to the overwhelming brightness of the sun, but as I learned yesterday it’s not that difficult if you have a plan and the right scope. Active observation is key. This made me think about the challenges of in-store sensing and of capturing shopper insights in general. Valuable observations don’t happen by accident; they are a result of carefully planned and executed practices. (*Props to the Yankee sage Yogi Berra.)

Some misses are forever. June 5 marked your last chance to see a transit of Venus. It won’t happen again until 2117. Luckily astronomers recorded this event, so you may watch the video. How many merchandising opportunities and rare marketing insights pass us by just like this? What can we do now to ensure that we don’t miss out on future learnings that may enable us to to be better prepared for the next window of opportunity? In retail merchandising and marketing, it begins with active sensing and collaborative data sharing.

Long cycles are hard to track. Under the most fortunate of circumstances, an individual astronomer gets to see the transit of Venus twice in a lifetime. Many never see it once. Even the lucky ones must count on other recorded observations to grasp its periodicity. With such a slow rhythm, it’s tough to draw reliable conclusions about the nature of the phenomenon. In the product marketing world, we discover that fast-turning consumable products offer some informational advantages as compared with infrequently purchased, higher consideration products, like cars, TVs and appliances. With many fewer data points and behaviors to draw upon, slow-moving consumer goods engender a less granular picture for marketers.

Sometimes you just need a team. Understanding the transit of Venus and its implications has required numerous observations separated by both time and physical distance. The relevant data has been collected by teams of scientists and coordinated among them with a common intent. Consumer insights also accumulate from observations collected across many locations and moments in time. You can’t unlock their potential alone. The implications are too vast, and the effort must be shared and sustained over time to reveal actionable insights and best practices.

The transit of shoppers through retail stores can reveal insights that we can best capture through systematic tracking and observation. When we can get the shoppers themselves engaged in documenting and sharing their actions and preferences as through mobile devices even greater wins are possible.

© Copyright 2012 James Tenser

The Optimization Arc – From Black Box to the Cloud

Joshua-CloudsWHEN THE GOOD FOLKS at DemandTec asked me to commence writing a series of short commentary pieces on this blog, I accepted the assignment in large measure because the company’s story is a reflection of the story of merchandising analytics in all its facets.

Like DemandTec, an IBM Company, my history as an analyst in what used to be called the “price optimization” sector dates back more than a decade. In 2002 I was asked to try to make this very powerful new retail science more accessible by explaining its benefits and justification in terms other than technical. Price optimization was a new idea, and its target purchasers were wary of its mysterious mechanisms.

Retailers’ objections about the apparent “black box” nature of base price elasticity permeated the sales cycles of industry pioneers, DemandTec’s included. Prospects worried that using computers to model price elasticity and interaction effects to maximize margins was too manipulative. What kind of push-back would they face if shoppers found out?

It took some effort at first, but we correctly reasoned that since optimization is based on measurements of shopper response, it is inherently shopper-centric in nature. Overall, the process tends to deliver more consistent competitive value to shoppers, while retailers maintain sustainable gross margins. These ideas are familiar now, but they were new territory ten years ago.

At about the same time, other pioneers began applying the principles of optimization to other complex merchandising decision processes, notably to the depth and timing of markdowns, and the terms of in-store promotions. Other folks were advancing assortment and space planning tools from the category management side of the house. Pretty soon, it dawned on the smarter people that that the interconnectivity and interaction effects they observed within each of these areas of discipline also exist across these areas of discipline; and not just within the retail organization, but between it and its trading partners.

A simple example might arise when a lower everyday price for a popular item revs up its turnover rate. The existing number of facings may become insufficient, creating intermittent out-of-stocks. The lost sales may tend to distort apparent demand and delay re-orders, and the problem perpetuates. Fold in other concurrent events within the category, such as new item cut-ins and shelf capacity constraints and the problem grows very knotty indeed.

Fly by Wire 

When I was first learning about all this, someone I respect explained to me why the mathematical model behind pricing optimization is related to the intricate “fly-by-wire” flight control systems that keep stealth aircraft from dropping out of the sky. Both critical objectives – keeping thousands of interrelated SKUs properly tuned, and keeping multiple interrelated flight surfaces properly tuned – share several traits:

  • The model is big
  • The model must be dynamic and continuous
  • The model must be highly reliable under duress
  • The model must be continuously updated at a time cycle that is rapid enough to support critical decision-making
  • The model must be appropriately accessible to decision makers

In one respect, those flight control systems may be simpler than retail demand models – there’s only one cockpit in an aircraft. A retail organization, by comparison, may have dozens or hundreds of individual decision makers and planners and trading partners interacting with the merchandising model through various dashboards. Each needs appropriate analytics and decision support according to his or her role.

To the Cloud 

As DemandTec developed and acquired its portfolio of software offerings over the past ten years, it placed evident emphasis on connecting users with the data and with each other in practical and beneficial ways. It was an early advocate of the software as a service (SaaS) application business model, which placed the heavy application power in outside computer servers, relieving clients from the burden of maintaining these systems in-house.

Lately the tech industry tends to refer to service-based computing as “the cloud.” In fact DemandTec’s current positioning, “The Collaborative Analytics Cloud,” reflects that. The explosive growth of major social networks has reinforced this concept, as have some of the largest IT companies. IBM, which acquired DemandTec last February, uses the tagline, “Smarter Commerce on Cloud” to describe its core strategic approach.

The company’s DemandTec Connect™social layer is a recent development in this regard. The platform leverages social-media-like interaction with embedded analytical applications to help shape collaboration across the merchandising ecosystem. Like any social media network, the platform is cloud-based. Its ability to provide role-appropriate access to a variety of optimization analytics is pure DemandTec.

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