Extraordinary In-Store Experience? Bet On New Service Behaviors!

If you never had the opportunity to listen Jeff Bezos I would strongly recommend to listen him here interviewed by Henry Blodget - founder and CEO of Business Insider (or, if you prefer to read the transcript of the interview, go here). 

There are many takeaways from the interview, but one that stands out to me most is this: “I’ve made billions of dollars of failures at Amazon. Literally billions of dollars of failures. You might remember Pets.com or Kosmo.com. It was like getting a root canal with no anesthesia. None of those things are fun. But they also don’t matter. What really matters is, companies that don’t continue to experiment, companies that don’t embrace failure, they eventually get in a desperate position where the only thing they can do is a Hail Mary bet at the very end of their corporate existence. One of my jobs is to encourage people to be bold. It’s incredibly hard. Experiments are, by their very nature, prone to failure. A few big successes compensate for dozens and dozens of things that didn’t work. Bold bets - Amazon Web Services, Kindle, Amazon Prime, our third-party seller business - all of those things are examples of bold bets that did work, and they pay for a lot of experiments.”

In the last couple of months, dozens - maybe hundreds - of articles have been written about Amazon's Acquisition of Whole Foods. Every observer is trying to find the rationale behind the acquisition, and now they are pondering who will be the next target.

Sources believe Amazon is interested in the furniture segment as well as appliances. I think Amazon is interested in those industries mainly because in those industries is notoriously difficult to shop and the reputation for customer service is somewhere between bad and nonexistent.

The unvarnished truth is that no one really knows what is in the Amazon’s mind or in which direction it will go. In fact, the retail industry’s failure to keep pace is that no one thinks like the Amazon founder.

Amazon hasn’t disrupted entire industries because of what they sell or even its prices. It’s a common misconception that they always have the cheapest prices around. They have a non-linear way of thinking that is not obvious to an industry like retail where executives rarely thinks in a non-linear way. In my opinion, Jeff Bezos doesn’t care if he sells you broccoli or shoes. Amazon is up for anything that broadens its reach.

This strategy of being the “everything store” will be the guiding principle behind the company’s search for additional acquisitions in its quest to become a vertical retailing monopoly.

In this strategy, the Whole Foods purchase is something like a test to see how well Amazon itself can ingest quickly and successfully another large company. Yes, you read correctly, it’s a “test”, a big bet - using Bezos’ words.

In other words, Amazon needs to test its ability to assimilate other companies. Some could say they already did that with the purchase of Zappos, Souq and Twitch. But those companies were startups and shared similar philosophies and experiences. I accept bets on how long before Bezos and John Mackey - Whole Food CEO - bump their heads. I personally believe that their claim of “love at first sight” will last until the ingestion will be complete. At that point, linear and non-linear head will crash one against the other, and ....guess whose head will survive?

Another great example of betting through experiments is provided by Hewlett Packard’s history. As remarkably reported by Peter Sims in his book “How breakthrough ideas emerge from small discoveries”, Bill Hewlett loved to make what he called “small bets” to uncover unpredictable opportunities. That approach helped HP pioneer handheld calculators. In 1972, HP’s first calculator, the HP-35, would retail at $400 at a time when the market for scientific calculators did not yet exist. The technology was remarkable and the calculator could fit into a pocket. But the price tag was hefty, especially at a time when the alternative was inexpensive slide rules. People inside HP were torn about what to do. So, they hired the leading market research firm specialized in computing research, which declared - after research - that nobody would buy the HP-35. Bill Hewlett wasn’t so sure. He had just spent several hours on a plane talking about the HP-35 with the person next to him, who thought it was amazing. Hewlett then suggested, “Why don’t we build a thousand and see what happens?”. It was an affordable bet. Within five months, HP was selling one thousand calculators a day and could barely keep up with the demand.

So, betting as the most important ingredient of non-linear way of thinking. In other words, companies competing in consumer markets have to experiment continously, embracing failure as founding paradigm of their culture

Actually, most companies competing in consumer markets act in a linear way, that is they plan instead of betting, they celebrate success instead of looking for failure. Consultants - I’m sorry for my well-respected collegues - are paid to support such wrong management style.

A typical exercise I do in workshops with C-level executives - that is aimed to introduce them to non-linear thinking - is what I call the “tropical water game business case”.

I introduce the workshop explaining that in tropical waters, cleaner fish remove parasites from the mouths of predators. The large fish attend “cleaning stations”, and the smaller fish that congregate there swim into their jaws. Having performed a prophylactic service as they eat their meal, the small fish swim out again unharmed. Actually, this phenomenon is hard enough to imagine, let alone invent, and nobody did invent it.

After the initial introduction, I normally ask to executives: “If you were recreating this ecosystem today to make it more efficent - magic word for executives’s ears - given what you know and given current technology, what would it look like?”.

Strange question, right?

Usually, somebody would lead to a recommendation that the predators should eat the cleaners. And this conclusion might be right. The more sophisticated would need to define and close the problem answering to some questions like: how large a group of predator fish normally is? Are their goals simply their own hygiene and nutrition? Do the predators have broader objectives: perhaps concerns for their reputation and the marine environment? The most sophisticated and data driven executives would recommend to collect data to assess the available feeding alternatives, for both cleaners and predators. A proper analysis would need to take also account of the subsequent effects on other marine species and the impact on predator’s welfare. Perhaps you can already envisage the PowerPoint presentation…

I don’t know what the answer to my question should be (!) although I am confident I could develop a model to deliver any answer my client wants. However, the value of such intervention in an environment in which there are multiple and conflicting objectives and an ecology of great complexity, is…zero. Nil. The only approach that might work is to try out incremental modifications - that is try different experiments - and see if they work.

I met only a very small minority of executives who jumped immediately to the final conclusion - that is try out incremental modifications. The large majority starts talking about which kind of data they need, how to collect those data, data analysis etc.

In other words, they are afraid to do a mistake! And this is due to the culture that permeates their companies. In those companies mistakes are the worst thing you can make, everybody is measured based only on success.

And what’s about conferences, seminars and the like: we only read or hear about success. The only topics of presentations and conversations are successful products, successful services and the successful people who’d made them happen. They are always a celebration of success.

I‘m so tired to hear only success stories. We glorify success so much but at the expense of demonizing failure. We learn nothing from success stories. It’s from failures, even disasters, that we learn!

In learning-obsessed organizations worry of failure doesn’t exist, people are constantly looking for failure as a way to learn something new and leaders are constantly incouraging “bold bets”.

“If you’re going to take bold bets, they’re going to be experiments. And if they’re experiments, you don’t know ahead of time if they’re going to work”, Bezos said.

Actually, almost all companies do the opposite: they try to predict the future. In these companies, when you are presenting a so called “business case” to get funded a new product, a new service or whatever “new” you want to develop, you have to provide precise answers to these questions:

• What will you create EXACTLY?
• How much will it cost?
• When will we achieve break-even?
• What will be the ROI?
• How about EBIT?
• What revenues do you expect in the upcoming five years?

And if the presentation of the business case doesn’t provide precise answers to the above questions, you are……up to you how to fill in the dots.

Coming back to the Amazon’s acquisition of Whole Foods, prices have been dropped in Whole Foods stores on the first day of Amazon’s official ownership (first day!). For some items prices have been reduced up to 43%.

Do you think they are able to predict the result?! It’s clearly an experiment. An experiment that could drive towards different pricing strategies, like, for instance, dynamic pricing, which could be a disruption on a massive scale for brick-and-mortar retailers.

The price sticker - that was introduced over a century ago - is seen by many as an inequitable “pricing strategy”. No doubt that Amazon would like to eliminate such standardized pricing.

In fact, why should consumers pay the same for fresh food in the afternoon or evening when it’s not as fresh as it was in the morning and why should a consumer who buys from one store religiously pay the same price as the consumer who doesn’t?

This could have a devastating effect on many retailers that compete largely on price and haven’t carved out any distinct store experience.

Amen

*****

So, the question is: How can a company competing in consumer markets encourage experimentation among its people? For instance, how a retailer can encourage experimentation among store managers, store associates and the like? Or, how a bank can encourage experimentation among branch managers and salespeople?

First of all a clarification. Here I do not refer to experiments based on the use of technology or advanced data analytics, neither experiments which require physical changes in the stores. That is, I do not refer to dynamic pricing experiments - done by Amazon millions of times per day - nor email campaigns with different offers to different market segments, nor online versus in-store pricing, nor different shelf-placements, nor different layouts etc.

I assume now you are wondering what I’m referring to.

I’m referring to experiments of different service behaviors and the evaluation of their effect on consumer emotions and finally on consumer purchasing behavior - mainly purchasing probability

To be more precise, I’m referring to service behaviors acted by a store associate, a salesperson, an after-sales technician, an “in store” event involving several persons, even a behavior acted by the customer himself during a service co-creation activity, etc.

With this clarification in mind, companies competing in consumer markets have to follow a few guidelines in order to design and execute service behavior experiments. Here are the most important ones - a part from the statistical rules that have to be always fulfilled.

• Leaders have to show enthusiasm in learning for learning's sake

Leaders have to keep a positive emotional tone and attitude, emphasizing effort, persistence and a preference for continous challenge.

For instance, when is the last time a sales executive has praised his salespeople to have learned something new as a result of a new behavior experiment? Not praised to have won a new customer or having achieved the monthly quota!

• There are clear small behavioral goals, even uncomfortable ones

As proved by research on deliberate practice, people’s self-efficacy is increased as they succeed at more and more challenging tasks. At the beginning provide a new small service behavioral task to be experimented with a clear goal to be measured. Gradually provide a sequence of different behavioral tasks to be experimented.

For instance, are you asking your sales assistants to experiment a specific closed question to improve the customer’s level of attention and exploration? Are you asking to experiment a specific body movement for welcoming a customer in the store? Then, are you asking to experiment a sequence of different questions and body movements?

• Immediate feedback

Focus your behavior experiments on settings in which customers respond immediately, on the spot. The most effective experiments involve behaviors that are acted together with an individual customer and the observation of his response. The experiments have to be designed in order to measure immediately the effect on purchasing behavior - rather than perceptions. Use also video to support behavior evaluation and feedback. Top-athletes - with their coaches - spend hours and hours looking themselves in videos, just to learn something new.

• There should not be any worry of failure

The goal of every experiment is to learn something valuable - irrespective of the experiment’s results. To put it simply, worry of failure should not exist when people are experimenting a new service behavior, and their leaders - as I wrote above - should always keep a positive emotional tone - even when the experiment produces a negative outcome. Involving teammates is very useful to keep a positive tone during experiments, providing opportunities for joint attention and joint collaboration among people belonging to the same team.

Are you asking for instance your salespeople to design together an experiment aimed to find how to behave during a difficult sales encounter?

*****

I have applied the above principles in several consumer centric transformation programs. For instance, in a program I’m running for a leading US retailer, I recently visited anonymously a large store in Chicago - just to check whether they were actually doing the service behavior experiments that have been planned. I was looking at men’s sportswear and a woman - a sales assistant - turned to me and asked, “Is this your first time at …?” I told her it was. She replied kindly, “We have one of the largest collections of Barbour sweaters anywhere in Chicago.”

She proceeded to walk over to the Barbour department and I followed as she told me a few facts about the brand. She asked if I was from Chicago and I told her I was Italian - from Milan, visiting Chicago for business. She looked really amused to know that I was Italian, and said that she had just visited Rome and Milan with her husband, as we approached the Barbour department.

“These are our most popular men’s sweaters in the store,” she said. I replied “I do not need a sweater, I have already so many”.

“Try them on”, she said. I countered, “I don’t care if they feel great, I’m not going to buy, I do not need a sweater”.

She persisted with a bit of a laugh, ”Try them on. I have clients who have 15-20 of these sweaters”. But again I stated firmly, “I didn’t come here to buy a sweater”.

“Try them on. The fit is everything. This size should be the right one for you”, she said, as she picked out one of my size. “This color will go with more”, she said as she handed the sweater to me to touch it. She brought me to the fitting room and said, “I’ll be back”.

Before I even looked in the mirror, I liked the sweater very much. As I came out she said, “Doesn’t it fit well?”. I had to agree.

“How long are you in town?”, she asked. “Just until tomorrow”, I replied. At that point she introduced herself by name, and ….obviously I had to present myself. “Amazing Alessandro, you have just been part of an experiment!”, she exclaimed.

The program was starting a roll out phase, and she had been trained by a store manager that was trained by me.

Are you wondering what was she experimenting?

Well, many C-level retail executives are convinced that shoppers should be let moving freely in the store just to see and touch the items stocked in the store. Merchandising, store atmosphere and the like will increase shoppers purchase probability. Under such approach sales associates have only to greet, keep eye contact and help the shopper when they are asked. Sometimes they get close to a shopper - randomly or on purpose, and ask: “Can I help you?”. If the answer is, “No, thank you”, they fly away.

The experiment is aimed to turn upside down what sales assistants normally do, to increase purchase probability. They have to proactively approach shoppers, having been trained to “push” them in the dressing room, because - as my research on shopper behavior clearly shows - almost 75 percent of buying decisions are taken in the fitting room. They apply a mixed behavior, with a fine line between pushy and determined.

They are also experimenting other service behaviors, like giving a store tour, using analogies when the shopper is trying an item, etc.

The results have been so far impressive. The stores with the highest number of executed experiments have shown a consumer emotional performance 60 percent higher than other stores, sales per ticket growth is almost 25 percent higher and NPS growth is three-fold higher.

*****

In today’s super-fast changing consumer markets, learning through experiments is the only way to learn faster than competitors. Service behavior experiments are an essential part of a “learning through experiments culture” which allows all companies competing in consumer markets to learn faster than competitors how to deliver an extraordinary service experience.

In these companies, leaders are continously encouraging people to experiment new service behaviors applying what I called the “new service behavior principle”. If there is a service behavior you have never executed, try it in front of the customer. Observe how the customer reacts and try again. Hundreds of times. You will be surprised by how fast you will learn how to deliver an extraordinary consumer experience.