In a recent interview on Bloomberg TV’s “Taking Stock with Pimm Fox,” APT CEO Anthony Bruce comments on how consumer-facing companies can measure the return on Facebook advertising dollars.

Word-of-mouth has always been a powerful way to influence buying behavior. In fact, a recent survey found that 83% of consumers change their decisions based on positive conversations with existing customers. Though consumers still often learn about where and what to buy directly through “word-of-mouth,” it is now easier than ever for them to access the opinions of thousands of their closest friends and acquaintances through online social networks. And everyone seems to have an opinion – many of which will influence purchasing behavior. Understanding how to leverage this new world of online research and chatter to drive sales is critical in succeeding in this evolving environment.

One of the latest online phenomenas is Pinterest, a social network, which allows users to create virtual bulletin boards of items and products they like. With roughly 10 million users, new reports indicate that Pinterst may be driving significant traffic to online retailers, with individuals actually looking to purchase some of the items they have discovered.

As consumers’ exposure to brands change, so to must retailers’ marketing strategies and budgets. Budgets previously allocated for print, radio, and TV advertising must make room for new outlets. But venturing into new mediums and developing new strategies brings up many questions that retailers must answer, such as:

• How do online ads affect in-store sales?
• On which social media sites, for which customers, and in which markets is advertising profitable?
• How can we best leverage new avenues of communication, such as Pinterest, to drive customers to our website and to our stores?
Answering these questions is critical to succeeding in the evolving retail climate.

This year in particular, retailers are having a difficult time understanding how much of their sales lifts can be attributed to better weather versus how much is simply due to the direct impact of a single initiative. Highly seasonal companies, like The Home Depot, have already reported stronger sales due to the influx of customers who were able to use their shovels for planting instead of clearing snow from their driveways.

With such drastic seasonal changes, the only way to find the true incremental impact of any initiative is to test it in a subset of your stores. “Test” doesn’t mean trying something in all of your stores in Phoenix and Michigan and comparing it to balance of chain. Dust storms in Phoenix and snow storms in Michigan would derail any hopes of an accurate read. In order to find the true cause-effect relationship between any initiative and key performance metrics, it is necessary to set up representative tests and to employ a scientifically-based control group strategy that has the potential to deliver highly statistically significant results.

Only through representative, scientific testing can companies really begin to understand the impact of their initiatives. Is it time to rethink what’s really causing your sales to change this year?

In 1995, corporate strategic planners were hardly shaking in their boots about the launch of Amazon.com, which at the time was primarily a bookseller. Now, with an annual revenue approaching $50 billion (it’s doubled since 2009), executives from companies such as Best Buy and The Home Depot are concerned. In fact, in June 2011, 20% of all online retail visits – 280 million — were to Amazon.com, with another 30% divided between the second and third largest e-tail sites, eBay and Alibaba, respectively.

Those are some daunting statistics, but if you’re a brick and mortar retailer, take comfort in knowing that traditional retailers have the ability to compete by leveraging a preexisting competitive advantage: multiple channels. These additional channels yield two key benefits:

• The ability to cross-sell between the digital world and physical locations, if implemented correctly, can give a significant lift to your business. Programs, such as “buy online, pick up in store” marry the convenience of online shopping with consumers’ “gotta have it now” perspective.  Meanwhile, as Darrell Rigby aptly explains in a recent Harvard Business Review article titled “The Future of Shopping,” there are boundless opportunities to use digital-based promotions (e.g. QR codes, location-based emails and texts, etc.) to sell products while the shopper is standing in the store.

• There is potential to create an outstanding and consistent personal customer experience across the channels. A customer who buys a laptop on Amazon, for example, has limited ability to get in-person support.  On the other hand, a customer who purchases that same computer on BestBuy.com or using Best Buy’s mobile app can take the computer into the physical store and talk to a member of the “Geek Squad.” Online-only retailers cannot compete with a personal and tactile customer experience, enhanced by a knowledgeable customer service team.

But wait a minute – is Amazon, the king of online retail, recognizing the importance of supporting their online presence with brick and mortar stores? You bet.

Reports recently surfaced that Amazon is exploring the possibility of opening physical locations, as Jeff Bezos and company have clearly become aware of the opportunity to enhance customer experience and cross-sell products.

Companies are latching on to the fact that better multi-channel retailing is the wave of the future, and choosing the best strategies in which to invest time and resources is critical. But since all markets, locations, and customers behave differently, companies that decide to test, learn, and choose the best rollout strategy will distinguish themselves from the crowd.

Do you remember twenty years ago when you were deciding between 20 or 40 MB of storage for your computer? Today, 2.5 quintillion (10^18) bytes of data are created every day, enough to fill your computer’s 250 GB hard drive about 10 trillion times daily! Experts estimate that 90% of all of the world’s data was created in the last two years, and the amount of data in existence will continue to grow at a mind-boggling 40% annual rate. So it’s no wonder that the McKinsey Quarterly is convinced that Big Data will become a new type of corporate asset that, if understood correctly, could lead to a serious competitive advantage.

People often throw around the term “Big Data,” but what exactly is it? Though there is no exact definition, the consensus opinion is that Big Data refers to datasets that are too large to work with in the absence of specialized database management tools.

And where does this data come from? Every time a retailer records a purchase, a customer uses a mobile application to research a product, or a tracker records the movement of an RFID chip as a SKU makes its way from inventory onto the shelf, there are hundreds, if not thousands, of data points recorded.

In the old days, there were two types of companies: those that collected data but didn’t know how to optimize its value, and those who didn’t collect it at all. As data center, inventory management, and transaction-level technologies have all rapidly improved over the last couple of decades, collecting and storing this Big Data is no longer a problem for leading retailers. Today, “how do we monetize it?” has become the million-dollar question. Merely having this data is not in itself useful, but the decisions that come from close analysis have the potential to be. Unfortunately, these decisions are often based on simple reports and correlations that are not scientifically sound. Sophisticated analytics can now not only show correlations, but can more accurately show cause-effect relationships. Companies that most successfully adapt to these new strategies will distinguish themselves from their competitors, leaving other retailers to wonder how they missed the boat.

Testing is the best way to leverage data to make accurate, targeted, and profitable decisions. The McKinsey Quarterly argues that “using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes.” Many retailers have already taken their analysis to the next level by testing key initiatives and making confident decisions based on the results. At a major US retailer, for example, there was a disagreement about the effectiveness of a Buy One Get One (BOGO) vs. 30% off price promotion.

Using scientific testing methods, the retailer discovered that BOGO led to higher incremental profits in lower income areas, whereas the 30% off promotion was more profitable in less competitive markets. Based on these results, the store was able to target promotions for specific stores and generate $3.2 million per year in additional profits. These kinds of results are now expected among innovative retailers who have leveraged their data to test important decisions.

As the economic recovery remains somewhere between anemic and lukewarm and raw material prices fluctuate with great volatility, it is safe to say that margin pressure is here for the long haul. In the face of this pressure, retailers who don’t fully realize the extractable value of their data will face grave headwinds as they watch their competition test and learn, and blow right past them.

Imagine this scenario: a shopper with a half-filled basket perusing the aisles of your store stops for a moment to inspect an item. She pauses, pulls out her smartphone, and, using one of many apps available for this purpose, scans the barcode pulling up a price comparison that spans both your nearby brick-and-mortar competitors, as well as online retailers.

Depending on what she saw, she may opt to buy out the stock, or, at the other extreme, walk out of the store, leaving her basket behind. Likely, she will simply not buy that item if the price differential is too high and her desire for immediacy too low.

While some shoppers have always compared prices, with nearly 70 million U.S. consumers armed with smartphones and a plethora apps, never has the barrier to price comparison been so low. As of July 2011, smartphone penetration hit 40% of the mobile market, while RedLaser, a popular barcode scanning app, has been downloaded an estimated 12 million times.

Retailers might ask themselves how this will impact their pricing decisions. Competitive pressures have always been a factor in the pricing decision, but, until the advent of online retail, shoppers were poorly equipped for the task. By bringing the price comparison into the store, smartphones and price checking apps represent a new level of pricing pressure. How should a retailer respond?

A solution may be another app.

Imagine that same shopper, perusing your aisles suddenly stopping to look at her smartphone – not a call or a text – but a push notification about a special promotion. Retailers have already started testing such apps that push offers to smartphone equipped shoppers hoping to drive sales. This past year, Best Buy partnered with ShopKick to test their location-based promotion system, where Best Buy customers with the ShopKick app are sent rewards and offered deals for visiting stores and perusing the aisles.

More recently, retailers have begun developing their own apps that allow shoppers to track shopping lists and scan barcodes to pull up reviews, recommendations, coupons, and more. For instance, Wal-Mart just announced that it has launched a mobile app to take advantage of the mobile trend.

With mobile retail traffic expected to double this holiday season, many retailers are wondering how to ride the mobile wave. But with mobile traffic currently accounting for only 9.6% of online sales as of October 2011, the opportunity may still be limited. While retailers are hopeful that mobile will be a boon, the economics are still unclear. For many retailers, developing your own app may not be an option, and deploying location-based promotion systems to your entire network may not make the hurdle (especially in areas with low mobile penetration). As always, testing out these options in a sub-set of your network if possible can help reduce the risk of such investments.

Recently, I had the pleasure of reading Jim Collins’s new book, “Great by Choice,” which prompted me to re-read his classic, “Good to Great.” In re-reading “Good to Great,” I noticed that many of the ideas that Mr. Collins espouses are applicable to retail organizations today.

One idea, “the genius of AND over the tyranny of OR,” is particularly timely.  A common refrain from senior leaders is that in today’s chaotic environment, there’s not enough time for structured decision-making; there’s not enough time for a test to complete before deciding on roll-out; there’s not enough time.  To survive, leaders quip, we are forced to react quickly. In other words, executives often settle for “we can be fast OR data-driven … but right now, we just have to be fast.”

This idea strikes me as poor thinking in two ways.  First, decisions driven by “gut” or anecdotal evidence are more likely to be incorrect.  The direct result of this approach is that value-destroying ideas are more likely to be rolled out, and value-creating ideas are more likely to be canned.  In this “tyranny of OR,” retailers are both more likely to make the wrong “call,” and doing so more rapidly.  This is a double whammy which compounds small problems into big ones.

Second, I fundamentally disagree with the idea that you can’t have both fast decision-making AND data-driven decision-making.  The solution to “fast AND data-driven” decision making is … planning.  To have the right answer in March, you need to be testing ideas in-market in January and February.  To have the right answers in August, you need to be testing ideas in-market in June and July.  So on and so forth.  Long-term planning is a discipline at which retailers excel.  Retail organizations routinely order product 6 – 18 months in advance.  Testing to drive innovation is no different.

One related and pernicious argument against planned-and-orderly-testing is that the business environment is changing too quickly, and that today’s results aren’t useful tomorrow.  Doubtless, trying to predict the general macro-economic environment is frustrating and challenging:  Will Greece eventually default and drag down Europe and the global economy? Will unemployment recover? Will there be any “shocks” that drive up fuel prices and drive down consumption? 

I don’t know and I don’t think anyone really knows. 

However, I do know exactly which solutions retailers will rely on to overcome any challenge: merchandising mix, pricing and promotions, marketing message, marketing vehicles, customer relationship, etc.  In other words, no one can predict the problems tomorrow will bring, but we know exactly what’s in the toolbox to fix these problems.  Isn’t it beneficial to sharpen our tools for whatever problems the future might bring?

We often commiserate in these posting about the difficulty of running a retail company.  But, fair-is-fair, and it’s important to highlight that some of these challenges are self-inflicted.  The lack of discipline in the decision-making process results in a cycle of poor outcomes and ever faster reactions to “fix” the problem.  Collins puts it bluntly, “Following the belief that leading a fast world always requires fast [and more likely inaccurate] decisions and fast [and likely misplaced] actions is a good way to get killed.”

Increasingly, retailers view their store labor as a cost center that needs to be optimized.  Labor, which runs 10 – 15% of sales, is usually the largest SG&A expense and an attractive target for cuts.   This strategy has been broadly adopted as attested to by the fact that retailers are significantly reducing their holiday hiring in 2011.

Beyond simply reducing labor, retailers are also aggressively “optimizing” how store labor is managed.  In the last few years, retailers have been quick to adopt software systems that automate task management, standards and models, and scheduling.  Rather than loosely defined task lists, store employees now work to achieve highly detailed assignments:  when exactly to restock shelves based on presentation levels, how long each customer should take in the check-out lane, how to reset layouts precisely based on plans, etc.

While both these changes have undoubtedly boosted “productivity,”  (i.e. staff has been reduced, and the remaining staff is better at completing “tasks”), it makes one wonder if taking these strategies to the extreme misses the “point” of having staff.  After all, isn’t the primary point of having store staff to “sell more through helping customers?”

Recent articles in the Economist and Harvard Business Review both tackle this question.  “The Art of Selling” describes how salespeople are maligned in a wide array of traditional industries, from pharmaceuticals to automobiles.  Even still, the author notes, sales plays a critical role in an enterprise, which is why even technology driven companies, like Google and Salesforce, have “thousands of flesh-and-blood” salespeople.

Similarly, the president of Office Depot, Kevin Peters, quips that the strategy that’s helping improve Office Depot is less stocking, more selling: “Many people think that … you need to hire more front-line workers.  [but] by finding ways to reduce time on functions like stocking shelves, we’ve been able to repurpose their time for selling to customers.”

He goes on to explain that simple changes in the way employees approach customers have resulted in dramatic improvements:

• Instead of asking “Hi, how are you?,” ask “What brings you to Office Depot today?”
• Instead of asking “Are you finding everything okay?,” ask “What can I help you find today?”
• Insead of asking “Is this all you need today?,” ask “What else are you looking for today?
• etc.

As with anything that’s based on the experience of another retailer, YMMV (your mileage may vary). Still, the point remains the same.  Rather than trying to reduce the check-out time by another 10 seconds (and driving the staff crazy in the process), shouldn’t retailers try instead to increase last minute basket add-ons by 5%?  Rather than trying to squeeze the last bit of efficiency from store staff, shouldn’t retailers try to help store employees get better at selling?  Rather than relentlessly driving down costs to boost productivity, shouldn’t retailers think more about growing sales to increase productivity?  Creating effective training programs for salespeople may be more difficult than explaining the optimal way to layout a shelf, but from what we can tell, the benefit is worth it.

Retailers have been keen proponents of always building it bigger. Many chains now have more than 100,000 square feet of selling space. In an ailing economy, these large stores face a double-whammy by having all that space: (1) to merchandise without appearing sparsely stocked, they have to carry a lot of low turnover inventory, and (2) large square footage destroys a key comparative metric that Wall Street values – sales per square foot.

Many large stores are looking to sublease some of this space. Stores are considering a variety of possible roommates: store-in-store, kiosks, outright leasing to other retailers. As stores consider these options, they should analyze three key questions:

1. Is the new kiosk/sub-store bringing in incremental profits? While it may seem like a new store-in-store concept will draw additional customers, retailers need to analyze what is the true incremental impact of a new sublease on four-wall profits. We have seen that some store-in-store concepts simply shift sales from an existing department to the new sub-store, without generating additional profits. Depending on the type of merchandise the new store offers, substitutability with current merchandise, and the potential for the new store to attract completely new customers to the main store – there is significant variation in impact of adding a sublease.
2. Which stores should get the new store-in-store? The impact of the store-in-store concept often varies significantly by market, demographics, and size of existing stores. Retailers thinking of introducing the store-in-store format should carefully test which of its current stores respond positively to a new sublease. Often subleased stores are rolled out based simply on the availability of space rather than robust analysis of various market-level factors that impact the sustainability of the new addition.
3. What sub-store format is most impactful? Decisions regarding the presentation of the sub store (kiosk vs. demarcated area etc.) need to be made after carefully considering how customers react to various formats. More often than not, sub-leases come in with a pre-planned format that is to be swallowed as is by existing stores. Not having the correct format makes it difficult to achieve the expected synergies between the two stores.

The easiest way to make the right decisions about these critical questions is to test the new sublease concept in a small group of stores before rolling them out broadly. Ultimately, having the right roommate makes things much easier. The wrong ones can create a lot of trouble.

Retail and consumer companies are rife with stories about highly fastidious founders.  A colleague recounted how he witnessed the head of a major chain of hotels getting on his hands and knees to personally check if the drip pans under the refrigerators were clean.  Similarly, Sam Walton was famous for flying a prop-plane from store to store, and along the way, touching down wherever he saw a promising empty lot for a new store.

Today, leaders need to look beyond physical sites, store managers, and DCs and apply that same discipline to other aspects of their business.  The foundation for good decision-making is data.

In today’s volatile environment, managers are adjusting their business in near real-time, and most initiatives require the cooperation of multiple groups and departments.  Operating a retail business without consistent, up-to-date, integrated data is challenging and error-prone.  Here are the details to focus on:

• Consistency:  Do finance, marketing, and merchandising have the same measure for sales … and margin?  While working with a major US retailer, we discovered numerous disparate systems for storing sales by item, by store.  Each had been setup for a unique purpose and required maintenance and reconciliation with other systems.  An inordinate amount of time was wasted in sharing across the organization (How do your numbers foot to the system that we use?) and caused a general reluctance for team-members to work across the organization.  There will be resistance to centralize – various dependencies will need to be rewritten – but this is problem only worsens with time.  Better to act now before it ossifies and becomes even more intractable

• Frequency: It’s no longer enough for managers to know today’s performance next week.  Understandably, the delay between the time something sells and when the data is ready for use exists for good reason.  Raw data needs to be audited and scrubbed for fraudulent accounts.  Late-breaking transactions need to be integrated.  Data is often augmented with additional information (e.g. mapping between credit card number and customer ID).  Even so, what managers should push for is making available data accessible immediately.  Sure, the data may have a few holes and analysts will need to be cautious, but generally speaking, the data is mostly right and giving managers the data a week early offsets any downside from the modest inaccuracies.

• Accessibility: Consistent, up-to-date data is of no use if it’s locked in a vault.  The gains from data come primarily in two ways: a) enabling a greater number of managers to make decisions in a data-driven way and b) allowing managers to have a more complete view of the business.  There are certainly some sensitive datasets (e.g. HR) that need to be carefully doled out.  But, in most cases, greater accessibility should be the goal.  This exposes a question about governance — what if users interpret data incorrectly to draw false conclusions — a real concern that warrants deeper discussion in a subsequent post.

Data, of course, is just the first step in building a robust retail organization … one that can nimbly “read the writing on the wall,” continually improve the business, and drive profitable innovation.  In subsequent articles, we’ll discuss the role of analytics and governance.