You ARE a technology company

In this day and age, pretty much every company is heavily dependent on technology to operate. But if you have an e-commerce operation (or really any sort of transaction website), you are a consumer technology company. The sooner we recognize and accept this fact, the sooner we can get on with leveraging it to our competitive advantage.

We often talk about focusing on our “core businesses” at the expense of everything else. At a conference I attended last week, I heard a number of speakers and attendees reference Amazon as a “technology company” as sort of a dismissal. They were basically saying, “Yes, Amazon has lots of great features and functionality and people rate their experience highly, but they’re a technology company. We’re retailers. We can’t compete on that level with them.” This type of statement draws the obvious retort: “So, then, on what level do you plan to compete?”

While Amazon does generate some revenue from selling technology services, the vast majority of their revenue comes from retailing products. Their financial statements look pretty much the same as most retailers (except they have much bigger numbers and growth rates). But Amazon and other pure play online retailers are not burdened with the type of legacy thinking that exists in a lot of multichannel retailers. They understand full well the value of creating a quality online experience, and they understand that technology is part of their core business.

Competing with Amazon is clearly very difficult for a variety of reasons (price being high on the list), but how many business elements can we abdicate to them before our very survival is at stake? Shifting our mindsets regarding our sites is one key way to claw back into the game.

Our websites are consumer software applications, in many ways like Microsoft Word or Quicken. And this means that online our business is technology.

People use our website applications to accomplish tasks like buying our products, learning more about our products or getting inspiration. Their perceptions about the quality of our applications can absolutely make the difference in whether or not they complete their tasks and whether or not they return to use our applications again.

And their perceptions of our brand can also be influenced by the quality of our site experiences. A study by ForeSee Results on the Internet Retailer Top 100 sites found that people who were satisfied with the online experience of a retailer were 44% more likely to purchase offline. That indicates significant value in making sure the website is a quality software experience.

Our websites are also an opportunity to differentiate from our competitors, particularly if we’re not selling proprietary products. If consumers can buy the same North Face jacket or Nikon camera from a variety of different retailers online, the quality of the online experience will be a contributing factor in the decision.

Let’s do what it takes to include the quality of our site experience in our value proposition.

Here are 3 ways to get started towards becoming a consumer technology company:

1. Organization
   We will likely need to make organizational structure changes to support a consumer technology focus. I previously made a case for changes in E-commerce IT organization that goes into more detail, but suffice to say the technology strategy and the business strategy need to be not only aligned, but integrated.

   Furthermore, we need think about different types of roles. Software companies have product — not project — managers and product teams who are dedicated to building customer focused product strategies and life cycles. A quick check on the Amazon careers page reveals many product management positions. Do you have product management positions in your organization?

   Check out a typical set of responsibilities from Amazon’s Baby Registry product management gig and note the mix of business and technology functions and responsibilities:

   • Research and identify opportunities for Amazon to further distinguish our Baby Registry offering.
   • Define a long-term product roadmap, including technical, business development and marketing initiatives.
   • Develop new strategic partnerships ad drive day-to-day partner relationships.
   • Conduct business and financial analysis, including forecasting, monitoring, and reporting.
   • Define requirements, and drive customer experience projects and work with all relevant cross-functional areas and our technology teams to guarantee smooth, efficient implementation.
   • Manage bottlenecks, provide escalation management, anticipate and make trade-offs, balance the business needs versus technical constraints, and maximize business benefit while building great customer experiences
   • Work cross-functionally with designers, software development engineers, salespeople, product managers, and other internal partners.

2. Budget/Investment
   How might our current budgets change if we considered ourselves  technology companies? Maybe not at all, but we should nonetheless re-examine our customer investment strategy in such a light. At the very least, we might consider revamping our budget processes to accommodate a fast moving, highly innovative competitive marketplace where the features and functionality of our website “product” are key parts of our business strategy and our ability to differentiate from our competitors.
3. In house 0r outsource?
   Often we decide to outsource technology (and other elements of our businesses) because they are not “core” to our business and other people can do a better and more cost effective job. How does our thinking on outsourcing change if we consider ourselves technology companies? We might still legitimately consider outsourcing or licensing third party software, as many software companies do. However, we might also consider building up true competencies in at least some areas of software design and development because of the need to differentiate and deliver quality branded experiences for our customers.

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Recognizing and accepting the fact that developing an e-commerce operation puts us in the consumer technology business is an important first step to successfully competing in the online marketplace. Once we’ve achieved the consumer technology mindset, we’ve got to take steps to create an organizational structure that executes like a consumer technology company. Without such steps, we will fall further and further behind the companies who are leveraging their technology focus to create the positive customer engagement cycles I discussed in my previous post.

What do you think? Do you think being in e-commerce means you’re in the in consumer technology business? How is your company organized?

Photo credit: Sebastian Bergmann

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?

My Favorite Sites of the Year

It’s the end of the year and the end of an amazing decade for e-commerce. So, in keeping with the time-honored tradition of awarding “bests” at the end of the year, I’m listing some of my favorites sites and site features of the year. I always enjoy discovering new sites and techniques when I read other people’s lists like this, so I hope you’ll find something interesting in my web award show.

The overall best e-commerce site award goes to:

Moosejaw.com

Moosejaw has it all. They’ve done an excellent job creating a very intuitive site that provides lots of options to narrow your selection; you can easily sort by price, color, size and brand. They have lots of what they call “custy reviews” available for their products, and you can even choose a “custy reviews” search/browse results page that highlights recent reviews in the product listing. Moosejaw has a great checkout process that does a good job of guiding the customer through the process, and their error messaging is clear and easy to understand. And no commentary on Moosejaw would be complete without mention of their Madness section, which is full of wacky content that keeps you coming back for more. In a final stroke of branding brilliance, Moosejaw provides free Moosejaw flags to anyone who requests them, and encourages people to take photos of themselves with Moosejaw flags at the height of their adventures, literally, like at the top of a mountain. What a brilliant way to make your customers your greatest marketers. As a final point of support for this award, when I asked people around the office for their favorites sites, Moosejaw was by far the most common choice.

Runner-up

Net-a-Porter

Net-a-Porter shows they understand how their customers shop, and they understand that the self-service experience of the web requires extra attention. They have a prominent “What’s New” section, and their landing pages get right to the products (without lots of “window” signs screaming about promotions). Each item in the listing has an alternate view when hovering over it, which is becoming fairly common, but Net-a-Porter uses and alternate view that features the item being worn rather than just showing it from the back. When you click through to the product pages, there are many more product views and some items have an excellent video of a model walking in the clothes so customers can see how the clothing looks in action. Finally, there are details about how items fit and an invitation to contact a “Fashion Advisor” for more help if you need it.

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Best use of video:

K-Swiss

I’ve always wondered why more sites don’t do what K-Swiss is doing with their product videos. Namely, use them as the primary image for the product when they’re available.

When you arrive at a product page that features a video (which, unfortunately, isn’t all of them) the video launches immediately and shows a model walking in the item. You can easily switch the view to see her walking from the front, from either side and from the back.  And best of all, there’s not sound that could get a workplace shopper in trouble. K-Swiss also features multiple static images of product to ensure customers are getting as much information as possible.

Runner-up

Ice.com

Ice.com is also making excellent use of video and using it as their primary image when a video is available. And they’re getting great results. Ice’s Pinny Gniwisch reports conversion rates jumping a whopping 400% after customers view a video, and return rates drop 25% for products with videos. Video really helps give customers a much better understanding of what they’re buying, which helps to remove one more barrier to purchasing products online. I’m really impressed with the quality of the short videos they’re producing, as well. The folks at Ice.com clearly understand the value of video, and they’re making the right investment to improve their business.

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Most interesting merchandising tool:

Polyvore

Polyvore is not a retailer, but that doesn’t mean there’s not something to learn from or leverage what they’re doing. They call themselves “a fashion community site that lets you mix and match products from any online store to create outfits or any kind of collage. It is also a vibrant community of creative and stylish people.” They have a really cool drag and drop capability that let’s visitors “create looks” from product feeds from many different retailers. Essentially, the visitors become merchandisers, and they’re looks are posted to be voted on and commented on by the community. The best looks rise to the top. There are some really amazing collections, and of course each product has a buy button. Polyvore is now making their technology available to retailers, as can be seen in Charlotte Russe “Design Your Outfit” section.

Runner up:

Hunch

Hunch is also not a retailer, but as with Polyvore, there’s lots to learn and leverage. Hunch describes themselves as “a decision-making tool that gets smarter the more you use it. After asking you 10 questions or less, Hunch will provide a concrete result for decisions of every kind.” Basically, they ask you a series of questions and then provide product recommendations that match. The general concept is not new, but Hunch’s implementation is the best I’ve seen and it gets better the more it’s used. They’re using the community to build and refine the question sets, and they’re covering a massive range of topics. The whole experience is really addictive.

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Most proactive:

Restaurant.com

Poorly written error messages are the bane of the web and a shameful way to lose sales, as I’ve previously discussed. But even well written error messages can be annoying because they come after the fact. Restaurant.com has taken a proactive approach in their account creation process. As a visitor enters a form field, a small box appears to the right giving the user detailed descriptions about what’s expected to be entered and, when appropriate, giving the reason why it’s important. Try it out to see how helpful it is.

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I could go on and on about lots of great features on a lot of different sites, but the seven above really stood out for me as great examples worth checking out.

But there are tons of great sites I haven’t even seen.

What sites stand out for you? I would be grateful if you’d use the comments section to share your favorites with the rest of us.

“Obscure and pregnant with conflicting meanings”

We’ve all heard the cliché “hindsight is 20/20” a thousand times. And it’s pretty much true. It’s a lot easier to figure out the path to a particular event when you know the final outcome. But if “what happened” is something bad, determining the reason after the fact doesn’t change the negative event.

How can we do a better job finding those problems in advance of our next new strategy implementation, site redesign, store remodel or other big effort?

It’s worth digging a little deeper to better understand why our hindsight is so perceptive. One of the most famous cases of 20/20 hindsight comes from the investigation into the attacks on Pearl Harbor (although, we could also argue the investigation into 9/11 and the more recent Fort Hood shootings have many similarities). In her book Pearl Harbor: Warning and Decision, noted military intelligence historian Roberta Wohlstetter wrote “it is much easier after the event to sort the relevant from the irrelevant signals. After the event, of course, a signal is always crystal clear; we can now see what disaster it was signaling since the disaster has occurred. But before the event it is obscure and pregnant with conflicting meanings.”

Of course, Pearl Harbor was an unexpected disaster that seemingly came out of nowhere. While we have those occasionally in business, more often than not our “disasters” come from strategies, redesigns or promotions that did not perform as expected. And those expectations can also lead to our blindness.

Whenever we’re implementing some new and exciting strategy, we tend to be very optimistic about the results. We’re convinced these new strategies are going to provide positive returns or we wouldn’t be implementing them. That optimism can lead to the same sort of crystal clear signal Wohlstetter referenced, but in the opposite direction; i.e. we tend to only see how everything we’re doing will lead to greatness and can easily overlook variables that have potential to lead to negative outcomes.

So, what do we do about it?

It seems some of the most common solutions today involve pulling together a committee to review what went wrong and putting together processes to prevent those specific problems in the future. These new processes don’t prevent all potential problems in the future, but with any luck they’ll prevent us from repeating the same mistakes.

But all of that happens after the fact.

There’s got to be a better way. My problem with the “committee and new process” approach is there’s a tendency to introduce lots of new and –all too often — needless bureaucracy. Inefficiencies ensue without greatly decreasing the probability of problem-free future efforts.

A technique I’ve found effective invokes much of the clarity of hindsight by drawing on the power of imagination.

During the ROI process for the strategy or project, we’ve already imagined the positive outcome. So before we wrap up planning, let’s also imagine a couple horrific scenarios. For example, imagine that four or five months after a site redesign, sales are down 50% and customer satisfaction has tanked. What happened? Now let’s assemble the same type of committee we would in that scenario and pour over the plan to find the causes of our imagined disaster.

Some might say this technique is really just standard contingency planning, but I find some pretty big differences. Contingency planning tends to look at the current plan to identify execution risks. It doesn’t often uncover key strategic or design problems.

The Scenario Imagination technique provides us with a different sort of lens that taps into our hindsight abilities to separate the signal from the noise.

We certainly won’t find every potential problem, but every problem we mitigate increases our probability of success and reduces our risk. And if we can reduce a lot of risk without strangling ourselves in bureaucracy, we’ll likely lower costs, increase efficiencies, and increase profits. I like the sound of that.

What do you think? Have you run into these types of issues? Do you think this technique would work for you? Do you have any techniques you would like to share?

Photo credit: me’nthedogs