Beyond the Buy Button: The Huge Additional Value of Retail Websites

Sometimes, I think we focus so intensely on the e-commerce sales of our sites that we miss the overwhelming additional value they bring to our businesses. Retail websites, particularly for multi-channel retailers, are more multi-dimensional than any other channel and any other brand vehicle. We fail to recognize the value of these sites beyond the buy button at our own peril.

Some are starting to see the additional value. During her presentation at the Retail Innovation and Marketing conference in San Francisco last week, Express Chief Marketing Officer Lisa Gavales talked about her epiphany surrounding Express.com’s value to the brand. It was Express.com’s traffic numbers that sparked the light bulb in her head. She realized that Express.com got as much traffic in a week as all of the Express stores combined. In other words, half of Express brand interactions were occurring on Express.com. Lisa immediately understood the marketing value of such high levels of engagements from Express’ customers. So much so, in fact, that she came to a conclusion she deemed controversial during her presentation — Express.com should be a marketing vehicle first and a direct sales channel second.

After the presentation, my good friend Scott Silverman, Shop.org’s Executive Director, asked me if I agreed with Lisa’s positioning of Express.com. I rambled on a bit before essentially saying “yes and no.” I’ll now take this space for what I hope is a more coherent answer.

I completely agree with Lisa that retail websites are much more valuable to the overall business than their direct sales indicate. Applying resources and strategic importance to sites based only on their percentage of sales is a mistake that could prove very costly in the long run. Customers use our sites for many reasons beyond direct transactions and our failure to highly prioritize those intentions is a disservice to our customers that will affect our bottom lines. But the value of our sites goes well beyond just marketing and direct sales and simply switching priorities is not enough. Furthermore, I worry that prioritizing marketing higher than everything else will lead to the types of conversion problems I previously discussed in my post “Conversion tip: Don’t block the product with window signs.”

Let’s consider some of the many values a retail website provides for a multi-channel retailer:

• Marketing vehicle
  As Lisa noted, the marketing value of our websites is immense. We are getting tons of traffic, and each engagement is an opportunity to enhance our brands. (Of course, if we’re not careful, the opposite is also true.) Websites are a highly efficient way to strengthen the Customer Engagement Cycle. Both online and offline marketing vehicles can direct customers to our sites to further enhance our messages. Our sites are also a great way to tell people about our stores on both a collective and an individual level.
• Merchandising vehicle
  Customers come in droves to our sites to learn more about the products we sell, whether they intend to buy online, over the phone or in our stores. Our sites have to essentially be our best and most knowledgeable merchants. They have to lead customers to the right products for them and provide the right information for them to make a selection, regardless of the channel where the purchase takes place.  This is a huge, often untapped, opportunity for quality merchants to reach their customers and sell them the right products.
• Customer research tool
  This is a bit of a double entendre. As mentioned above, our customers are certainly using our sites for their research. But we can also use our sites to learn more about our customers. There is a wealth of information to be had about what our customers are doing and what they desire. Not only can we see what they purchase, but we can also use web analytics to see what they look at. With tools like those provided by ForeSee Results (shameless plug), we can also know what they are thinking, what they are intending to do, and how they are perceiving our brands. All of this can be done fairly easily and inexpensively in ways that are either impossible or impossibly expensive in the physical world.
• Customer relationship enabler
  We can continue to build relationships with our customers by applying what we’ve learned above to give them better experiences. The applied knowledge of our merchants combined with the long-lasting memory of our websites should allow us to constantly serve our customers better. As we focus on building those relationships with more personalized site experiences, more informed personal interactions via contact centers and in-store, and more relevant email and direct mail communications, we will build stronger loyalty with our customers.
• Community builder
  Websites also give us ways to connect our customers with each other. Our brands can act as a central hub for like-minded customers to find each other and help each other find products that meet their needs or solve their problems. How great is that? We can make these connections both via our own sites and via social networks like Facebook. Either way, it’s another way for our brands to provide services for our customers. Our sites can also allow our brands to be more localized by providing additional vehicles for our stores to connect with their communities.
• Sales driver — in-store and online
  And, of course, we can sell stuff. We can sell lots and lots of stuff online. Our sites are still not where they need to be for maximum usability, so we have plenty of opportunities to improve their ability to sell directly. But we also have lots and lots of opportunity to drive traffic into our stores. We can show inventory; we can let people buy or reserve online and pick up in-store; we can host coupons;  we can help people find a store close to them; we can provide reviews and recommendations to people standing in our stores (whether via kiosks or mobile phones). The possibilities are endless.

These site values are not mutually exclusive. Their value in combination is exponentially higher than any one individual value. Therefore, it’s critically important to consider our sites holistically when determining their place and priority in our strategic plans. We need to consider their combined value when we determine allocation of resources and organizational structure.

Too often, though, resources and executive attention are not apportioned to the site according to this additional value. And we often don’t even measure these additional value points (which might explain the lack of resources and executive attention). If our most important measures of our sites revolve solely around direct sales, we will continue to minimize the importance of all other values of our sites.

I believe the multichannel retailers with the brightest futures in this new decade will be those who fully embrace and leverage the multi-dimensional value of their websites.

What do you think? How is your site valued in your organization? What retailers do you think are most recognizing the additional value of their sites?

The Missing Links in the Customer Engagement Cycle

The Customer Engagement Cycle plays a central role in many marketing strategies, but it’s not always defined in the same way. Probably the most commonly described stages are Awareness, Consideration, Inquiry, Purchase and Retention. In retail, we often think of the cycle as Awareness, Acquisition, Conversion, Retention. In either case, I think there are a couple of key stages that do not receive enough consideration given their critical ability to drive the cycle.

The missing links are Satisfaction and Referral.

Before discussing these missing links, let’s take a quick second to define the other stages:

Awareness: This is basic branding and positioning of the business. We certainly can’t progress people through the cycle before they’ve even heard of us.

Acquisition: I’ve always thought of this as getting someone into our doors or onto our site. It’s a major step, but it’s not yet profitable.

Conversion: This one is simply defined as making a sales. Woo hoo! It may or may not be a profitable sales on its own, but it’s still a significant stage in the cycle.

Retention: We get them to shop with us again. Excellent! Repeat sales tend to be more profitable and almost certainly have lower marketing costs than first purchases.

Now, let’s get to those Missing Links

In my experience, the key to a strong and active customer engagement cycle is a very satisfying customer experience. And while the Wikipedia article on Customer Engagement doesn’t mention Satisfaction as often as I would like, it does include this key statement: “Satisfaction is simply the foundation, and the minimum requirement, for a continuing relationship with customers.”

In fact, I think the quality of the customer experience is so important that I would actually inject it multiple times into the cycle: Awareness, Acquisition, Satisfaction, Conversion, Satisfaction, Retention, Satisfaction, Referral.

Of course, it’s possible to get through at least some of the stages of the cycle without an excellent customer experience. People will soldier through a bad experience if they want the product bad enough or if there’s an incredible price. But it’s going to be a lot harder to retain that type of customer and if you get a referral, it might not be the type of referral you want.

I wonder if Satisfaction and Referral are often left out of cycle strategies because they are the stages most out of marketers’ control.

A satisfying customer experience is not completely in the marketer’s control. For sure, marketing plays a role. A customer’s satisfaction can be defined as the degree to which her actual experience measures up to her expectations. Our marketing messages are all about expectations, so it’s important that we are compelling without over-hyping the experience. And certainly marketers can influence policy decisions, website designs, etc. to help drive better customer experiences.

In the end, though, the actual in-store or online experience will determine the strength of the customer engagement.

Everyone plays a part in the satisfaction stages. Merchants must ensure advertised product is in stock and well positioned. Store operators must ensure the stores are clean, the product is available on the sales floor and the staff are friendly, enthusiastic and helpful. The e-commerce team must ensure advertised products can be easily found, the site is performing well, product information in complete and useful,  and the products are shipped on time and in good condition.

We also have to ensure our incentives and metrics are supporting a quality customer experience, because the wrong metrics can incent the wrong behavior. For example, if we measure an online search engine marketing campaign by the number of visitors generated or even the total sales generated, we can absolutely end up going down the wrong path. We can buy tons of search terms that by their sheer volume will generate lots of traffic and some degree of increased sales. But if those search terms link to the home page or some other page that is largely irrelevant to the search term, the experience will be likely disappointing for the customer who clicked through.

In fact, I wrote a white paper a few months ago, Online Customer Acquisition: Quality Trumps Quantity, that delved into customer experience by acquisition source for the Top 100 Internet Retailers. We found that those who came via external search engines were among the least satisfied customers of those sites with the least likelihood to purchase and recommend. Not good. These low ratings could largely be attributed to the irrelevance of the landing pages from those search terms.

Satisfaction breeds Referral

Referrals or Recommendations are truly wonderful. As I wrote previously, the World’s Greatest Marketers are our best and most vocal customers. They are more credible than we’ll ever be, and the cost efficiencies of acquisition through referral are significantly better than our traditional methods of awareness and acquisition marketing. In my previously mentioned post, I discussed some ways to help customers along on the referral path. But, of course, customers can be pretty resourceful on their own.

We’ve all seen blog posts, Facebook posts or tweets about bad customer experiences. But plenty of positive public commentary can also be found.  Target’s and Gap’s Facebook walls have lots of customers expressing their love for those brands. Even more powerful are blog posts some customers write about their experiences.  I came across a post yesterday from entitled Tales of Perfection that related two excellent experiences the blogger had with Guitar Center and a burger joint called Arry’s. Both stories are highly compelling and speak to the excellent quality of the employees at each business. Nice!

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Developing a business strategy, not just a marketing strategy, around the customer engagement cycle can be extremely powerful. It requires the entire company to get on board to understand the value of maximizing the customer experience at every touch point with the customer, and it requires a set of incentives and metrics that fully support strengthening the cycle along the way.

What do you think? How do you think about the customer engagement cycle? How important do feel the customer experience is in strengthening the cycle? Or do you think this is all hogwash?

Why most sales forecasts suck…and how Monte Carlo simulations can make them better

Sales forecasts don’t suck because they’re wrong.  They suck because they try to be too right. They create an impossible illusion of precision that ultimately does a disservice to managers who need accurate forecasts to assist with our planning. Even meteorologists — who are scientists with tons of historical data, incredibly high powered computers and highly sophisticated statistical models — can’t forecast with the precision we retailers attempt to forecast. And we don’t have nearly the data, the tools or the models meteorologists have.

Luckily, there’s a better way. Monte Carlo simulations run in Excel can transform our limited data sets into statistically valid probability models that give us a much more accurate view into the future. And I’ve created a model you can download and use for yourself.

There are literally millions of variables involved in our weekly sales, and we clearly can’t manage them all. We focus on the few significant variables we can affect as if they are 100% responsible for sales, but they’re not and they are also not 100% reliable.

Monte Carlo simulations can help us emulate real world combinations of variables, and they can give us reliable probabilities of the results of combinations.

But first, I think it’s helpful to provide some background on our current processes…

We love our numbers, but we often forget some of the intricacies about numbers and statistics that we learned along the way. Most of us grew up not believing a poll of 3,000 people could predict a presidential election. After all, the pollsters didn’t call us. How could the opinions of 3,000 people predict the opinions of 300 million people?

But then we took our first statistics classes. We learned all the intricacies of statistics. We learned about the importance of properly generated and significantly sized random samples. We learned about standard deviations and margins of errors and confidence intervals. And we believed.

As time passed, we moved on from our statistics classes and got into business. Eventually, we started to forget a lot about properly selected samples, standard deviations and such and we just remembered that you can believe the numbers.

But we can’t just believe any old number.

All those intricacies matter. Sample size matters a lot, for example. Basing forecasts, as we often do, on limited sets of data can lead to inaccurate forecasts.

Here’s a simplified explanation of how most retailers that I know develop sales forecasts:

1. Start with base sales from last year for the the same time period you’re forecasting (separating out promotion driven sales)
2. Apply the current sales trend (which is maybe determined by an average of the previous 10 week comps). This method may vary from retailer to retailer, but this is the general principle.
3. Look at previous iterations of the promotions being planned for this time period. Determine the incremental revenue produced by those promotions (potentially through comparisons to control groups). Average of the incremental results of previous iterations of the promotion, and add that average to the amount determined in steps 1 and 2.
4. Voilà! This is the sales forecast.

Of course, this number is impossibly precise and the analysts who generate it usually know that. However, those on the receiving end tend to assume it is absolutely accurate and the probability of hitting the forecast is close to 100% — a phenomenon I discussed previously when comparing sales forecasts to baby due dates.

As most of us know from experience, actually hitting the specific forecast almost never happens.

We need accuracy in our forecasts so that we can make good decisions, but unjustified precision is not accuracy. It would be far more accurate to forecast a range of sales with accompanying probabilities. And that’s where the Monte Carlo simulation comes in.

Monte Carlo simulations

Several excellent books I read in the past year (The Drunkard’s Walk, Fooled by Randomness, Flaw of Averages, and Why Can’t You Just Give Me a Number?) all promoted the wonders of Monte Carlo simulations (and Sam Savage of Flaw of Averages even has a cool Excel add-in). As I read about them, I couldn’t help but think they could solve some of the problems we retailers face with sales forecasts (and ROI calculations, too, but that’s a future post). So I finally decided to try to build one myself. I found an excellent free tutorial online and got started. The results are a file you can download and try for yourself.

A Monte Carlo simulation might be most easily explained as a “what if” model and sensitivity analysis on steroids. Basically, the model allows us to feed in a limited set of variables about which we have some general probability estimates and then, based on those inputs, generate a statistically valid set of data we can use to run probability calculations for a variety of possible scenarios.

It turns out to be a lot easier than it sounds, and this is all illustrated in the example file.

The results are really what matters. Rather than producing a single number, we get probabilities for different potential sales that we can use to more accurately plan our promotions and our operations. For example, we might see that our base business has about a 75% chance of being negative, so we might want to amp up our promotions for the week in order have a better chance of meeting our growth targets.  Similarly, rather than reflexively “anniversaring” promotions, we can easily model the incremental probabilities of different promotions to maximize both sales and profits over time.

The model allows for easily comparing and contrasting the probabilities of multiple possible options. We can use what are called probability weighted “expected values” to find our best options. Basically, rather than straight averages that can be misleading, expected values are averages that are weighted based on the probability of each potential result.

Of course, probabilities and ranges aren’t as comfortable to us as specific numbers, and using them really requires a shift in mindset. But accepting that the future is uncertain and planning based on the probabilities of potential results puts us in the best possible position to maximize those results. Understanding the range of possible results allows for better and smarter planning. Sometimes, the results will go against the probabilities, but consistently making decisions based on probabilities will ultimately earn the best results over time.

One of management’s biggest roles is to guide our businesses through uncertain futures. As managers and executives, we make the decisions that determine the directions of our companies. Let’s ensure we’re making our decisions based on the best and most accurate information — even if it’s not the simplest information.

What do you think? What issues have you seen with sales forecasts? Have you tried my example? How did it work for you?

“If it ain’t broke, you ain’t looking hard enough”

The poor economy has done nothing to lower customer expectations of online retailers, and recent mixed results data from ComScore and ForeSee Results indicate that retailers who continue to improve their customer experiences are pulling away from their competitors in both sales and customer satisfaction.

ComScore reports online retail up 4% for the holiday season. While an increase is always nice, this is a much lower growth rate than online retail has seen in the past. And last year’s comparison base was far from stellar. ForeSee Results shows a significant drop in customer satisfaction year over year. Since satisfaction is predictive of future financial results, a drop is concerning.

But still, I wondered how sales could be up at all if satisfaction was so far down.

A deeper look at the ComScore data shows the Top 25 retailers growing 13% while “Small and Mid Tail” retailers are declining 10%. Satisfaction scores are also split, but the differences we’re seeing seem to be more based on those retailers who are continually improving their sites versus those whose cost containment measures have slowed or stopped improvements. It appears that the retailers who closely measure the effectiveness of their sites from their customers’ perspectives and continuously improve their customers’ experiences are the retailers with increasing customer satisfaction scores. Those retailers who didn’t improve customer experience this year are suffering declining satisfaction scores. Many of those in the Top 25 are the retailers who have continued to enhance their customer experiences. Those enhancements are not only helping them to increase their sales, but because of the high visibility and usage of those tops sites, they’re also raising consumer expectations of all sites.

Customer satisfaction can be best defined as the degree to which a customer’s actual experience meets his or her expectations. Therefore, rising expectations can depress satisfaction scores if customer experience improvements don’t keep pace.

In the rapidly changing world of online retail, stopping or delaying improvements is like treading water in a swimming race. While you may temporarily save some energy, you will fall hopelessly behind and your only hope of catching up is spending a lot more energy than you likely saved treading water

Growing online retail businesses realize and fully embrace the need for continuous improvements, and they also realize that online retail in general is far from producing the level of customer experience truly necessary to provide excellent self-service shopping experiences. I recently heard Robin Terrell, Managing Director of John Lewis Direct in the UK (and Amazon alum), say “If it ain’t broke, you ain’t looking hard enough” in a talk about the need to improve customer experience. It’s a brilliant statement, and I totally agree with what he was saying.

So, “improving customer experience” is a huge and vague statement. Where do we start?

1. Recognize that it’s broke and you ain’t looking hard enough
   We’re still in our infancy in online retail, and we’ve got a long way to go. We too often try to increase our sales by generating more traffic and don’t spend enough time converting the traffic we’re already got. Often, the obstacles to conversion are not the big, shiny, whiz bang functionality; they’re lots of little things that add up to big problems. Those problems are hard to see without a concerted effort, as I discussed in more detail in my Tree Stump Theory post and other posts on conversion.
2. Truly learn how effective your site is from your customers’ perspective
   We can all identify lots of improvements we’d like to see on our sites, but it’s the improvements our customers most need that will drive our best growth. So understanding where we are and aren’t effective from our customers’ perspectives is critically important, but difficult.Focus groups and usability labs can be very helpful, but they can’t be our first or only methodology because it’s not possible to project learnings from a small group of people onto our entire population of customers.

   First, we need to quantitatively understand our effectiveness in the eyes of our total population, and that requires a statistically solid customer polling and analysis capability. Blatant and shameless plug alert: I’ve had great success using ForeSee Results in the past for exactly this purpose. Once we understand problem areas at a macro level, we can add a lot of color by interacting directly with customers in focus groups and usability labs. More details on this process can be found in my post entitled “Is elitism the source of poor usability?”

3. Consider getting some help from usability professionals
   Usability audits are different from usability labs. Usability auditors are professionally trained to understand how people interact with websites. Many of them have degrees in Human-Computer Interaction, a field that truly seeks to understand how people interact with software. These types of people can really help to identify problems with our user interfaces that untrained eyes have trouble seeing but which regularly obstruct customers from accomplishing their tasks.
4. Put in place a process to continuously improve
   This is really about budgetary and project management mindset. We must just accept the fact that we can’t tread water in a never-ending swimming race, and our only chance of competing is to keep swimming. We have to build our staffs, our budgets and our processes with the recognition that competing in the marketplace means continuously improving our customer experiences. Which leads to …
5. Wash, rinse, repeat
   Since the leaders in the marketplace are running this same cycle, we cannot rest. We must continue to recognize our sites are broken, continue to measure our effectiveness from our customers’ perspectives, find problems, fix them and begin again.

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We’ve got a lot of data that shows that retailers who best satisfy their customers generate the best financial results. I suppose that statement doesn’t sound like rocket science. But understanding that satisfaction has a direct relation to expectations and that our customers’ expectations can change independent of what we do on our own site is important. The leaders are continuously improving their sites, and they’re improvements are raising our customers’ expectations. We’ve all got to swim harder to keep pace.

What do you think? What’s your view on the marketplace? How have you see customer satisfaction affect your business?

Are web analytics like 24-hour news networks?

We have immediate access to loads of data with our web sites, but just because we can access lots of data in real time doesn’t mean we should access our data in real time. In fact, accessing and reporting on the numbers too quickly can often lead to distractions, false conclusions, premature reactions and bad decisions.

I was attending the web-analytics-focused Semphonic X Change conference last week in San Francisco (which, by the way, was fantastic) where lots of discussion centered around both the glories and the issues associated with the mass amount of data we have available to us in the world of the web.

Before heading down for the conference breakfast Friday morning (September 11), I switched on CNN and saw — played out in all their glory on national TV — the types of issues that can occur with reporting too early on available data.

It seems CNN reporters “monitoring video” from a local TV station saw Coast Guard vessels in the Potomac River apparently trying to keep another vessel from passing. They then monitored the Coast Guard radio and heard someone say, “You’re approaching a Coast Guard security zone. … If you don’t stop your vessel, you will be fired upon. Stop your vessel immediately.” And, for my favorite part of the story, they made the decision to go on air when they heard someone say “bang, bang, bang, bang” and “we have expended 10 rounds.” They didn’t hear actual gun shots, mind you, they heard someone say “bang.” Could this be a case of someone wanting the data to say something it isn’t really saying?

In the end, it turned out the Coast Guard was simply executing a training exercise it runs four times a week! Yet, the results of CNN’s premature, erroneous and nationally broadcast report caused distractions to the Coast Guard leadership and White House leadership, caused the misappropriation of FBI agents who were sent to the waterfront unnecessarily, led to the grounding of planes at Washington National airport for 22 minutes, and resulted in reactionary demands from law enforcement agencies that they be alerted of such exercises in the future, even though the exercises run four times per week and those alerts will likely be quickly ignored because they will become so routine.

In the days when we only got news nightly, reporters would have chased down the information, discovered it was a non-issue and the report would have never aired. The 24-hour networks have such a need for speed of reporting that they’ve sacrificed accuracy and credibility.

Let’s not let such a rush negatively affect our businesses.

Later on that same day, I was attending a conference discussion on the role of web analytics in site redesigns. Several analysts in the room mentioned their frustrations when they were asked by executives for a report on how the new design was doing only a couple of hours after the launch of new site design. They wanted to be able to provide solid insight, but they knew they couldn’t provide anything reliable so soon.

Even though a lot of data is already available a couple of hours in, that data lacks the context necessary to start drawing conclusions.

For one, most site redesigns experience a dip in key metrics initially as regular customers adjust to a new look and feel. In the physical retail world, we used to call this the “Where’s my stuff?” phenomenon. But even if we set the initial dip aside, there are way too many variables involved in the short term of web activity to make any reliable assessments of the new design’s effectiveness. As with any short term measurement, the possibilities for random outliers to unnaturally sway the measurement to one direction or another is high. It takes some time and an accumulation of data to be sure we have a reliable story to tell.

And even with time, web data collection is not perfect. Deleted cookies, missed connections, etc. can all cause some problems in the overall completeness of the data. For that matter, I’ve rarely seen the perfect set of data in any retail environment. Given the imperfect nature of the data we’re using to make key strategic decisions, we need to give our analysts time to review it, debate it and come to reasoned conclusions before we react.

I realize the temptation is strong to get an “early read” on the progress of a new site design (or any strategic issue, really). I’ve certainly felt it myself on many occasions. However, since just about every manager and executive I know (including myself) has a strong bias for action, we have to be aware of the risks associated with these “early reads” and our own abilities or inabilities to make conclusions and immediately react. Early reads can lead to the bad decisions associated with the full accelerator/full brake syndrome I’ve referenced previously.

We can spend months or even years preparing for a massive new strategic effort and strangle it within days by overreacting to early data. Instead, I wonder if it’s a better to determine well in advance of the launch — when we’re thinking more rationally and the temptation to know something is low — when we’ll first analyze the success of our new venture. Why not make such reporting part of the project plan and publicly set expectations about when we’ll review the data and what type of adjustments we should plan to make based on what we learn?

In the end, let’s let our analysts strive for the credibility of the old nightly news rather than emulate the speed and rush to judgment that too often occurs in this era of 24-hours news. Our businesses and our strategies are too important and have taken too long to build to sacrifice them to a short-term need for speed.

What do you think? Have you seen this issue in action? How do you need with the balance between quick information and thoughtful analysis?

Photo credit: Wikimedia Commons