Introduction My name is Gregory Yankelovich. I was born and raised in Moscow at the time when "Customer Service" was an unknown concept. When I emigrated from Soviet Union "Customer Focus" became my religion. I have earned degrees in Economics,Industrial Engineering and Transportation Engineering, with post-graduate degree in Operations Research. During the length of my career, I have been involved with product management responsibilities in B2B and B2C markets, for both hardware and software products. For 18 years before starting Amplified Analytics, I specialized in customer centric technologies and solutions. I led dozens of Marketing, Customer Support and Sales automation projects and became acutely aware how little enterprise knows about people who use their products.
During this session we are going to address these basic premises
Peter Drucker is widely considered to be a father of Management Science. He affirmed that Most companies do not sell what customers buy, and that the goal of Product Management practitioners is to gain intimate knowledge of their target customer’s needs and empathy for their journey to achieve their desired objectives. These ideas inspired us to create the tools and methodology for product planning processes supported by customer focused data.
Today we will talk about leveraging customer feedback for validation of our product ideas. On the surface it doesn't sound like a new approach, but the iPod was not a first attempt to conquer portable music market either. There is a sufficient difference between bad ideas and good ideas that are poorly executed. It is very hard to give example of a bad idea without getting into very controversial subjects, so I will try to come up with something very obvious to most people.
Some of you may remember the Bob.Bob, like a politician would always pop up when you don’t need him, to give you a useless advice you don’t want. An interruption of the customer on his journey to the desired outcome is a very BAD idea. The other examples speak for themselves. I am reasonably sure that there was a panel or survey that provided validation for these great ideas and I would love to learn the ratio of actual sales to the forecast for these products.
Could it be that Steve and Henry were askingthe wrong questions? Or asked the wrong target customers? Perhaps one way to look at it is to say that customers cannot articulate requirements for a product they want, before they experience it. Both Henry and Steve believed that great products are the results of intimate understanding of their customers. There are many quotes can be found to illustrate that belief. However customer adoption of their products is the best proof. Personally, I think they warned us that surveys and focus groups are not the right approach to develop empathy for your customers.
A Survey starts with questions. The questions are loaded with a bias, our bias. Even the selection of which questions to ask immediately introduces the bias of theselector. We like to ask questions about functions and features because we understand a product as an aggregate of functions and features. We like to ask "on the scale from 1 to 5…?" because it is easy for us to tabulate answers and compare the test group results. Since a bias is unavoidable and we want to understand customer needs, perhaps it would be more logical to agree that customer bias is more valuable than ours in developing that empathy. Forget your questions and scales. Just let them talk.
Listening to peoples stories is a great start to developing empathy with …. the human race. However we want an intimate understanding of our target customers, which is a much smaller subset of humanity. Now it is the time to introduce a filter or bias. Customers see a product not as an aggregation of features and functions, but as means to achieve a desired outcome, for which they consider to buy this product. In other words - customers "hire" a product for a "job". Therefore we only want to hear the stories about the "jobs" our product could possibly be "hired" for. We are all familiar with a job hunting. This filter may produce a very large set of "stories" that involve products that we did not previously consider our competitors.
Clayton Christensen is a Harvard Business School professor and the author of many books on subject of Disruptive Innovation. He told a great story about a consulting gig with a fast food chain that wanted to sell more milk shakes. I would recommend listening to him telling the story because my storytelling skills are vastly inferior to his. However the gist of the story is that no amount of analysis, experimentations and surveys could help them answer how to increase the sales of that shake until they heard when, why and under what circumstances customers have bought it in the past. Focusing on a "job" allows us to isolate correctly our target customers. Listening to their stories allows us to learn their experience with the products, available to them currently to achieve their desired outcome.Analyzing their past experiences allows us to decide if our proposed product can simplify their experience.
It is commonly used argument that Apple does not use market research. I have no private, inside information to counter this argument, however a cursory search of Apple employees directory reveals a small army of specialists with titles like Consumer Insights, Customer Intelligence, etc. The analysis of job descriptions for Apple Market research positions indicates heavy emphasis on ethnographic research skills. The second quote on this slide illustrates my point.Ethnography involves actual observation and analysis of how people use products. It is a part of qualitative research and one of the most difficult and expensive methodologies in the field. On one hand it can produce the best, most valuable insights. On the other hand it is very expensive and does not produce statistically representative volumes of findings. Therefore the results are often challenged as being anecdotal, in other words, not trustworthy or scalable enough.
I bet Marketing Strategy folks at Apple just love you using this argument.Perhaps this argument should be framed differently "Apple does not buy Market Research" from external agencies. That means the most successful company in Consumer Product marketing considers Market Research to be one of their core competencies.
Most of us do not have the resources and budgets of Apple, or time to conduct exhaustive studies, particularly in the earlier stages of testing our brilliant ideas. Procuring, reading and analyzing volumes of customer stories sounds a lot like mining for gold. I know that some of you have spent hours on occasion reading survey comments and online customer reviews, to get a feel for your customers’ experience. I am not sure if you managed to learn anything of meaning that you did not already know, and considered this a good investment of your time. However if you did, I bet you will agree that it is not a scalable process or a process that can be delegated and outsourced. Fortunately advances in "big data", natural language processing, and opinion mining technologies can help with a heavy lifting, to filter what is important to customers. However I would like to warn that even the best tools cannot substitute lack of skills and the best technology cannot bridge the absence of method and process. Both are absolutely necessary to produce quality result - substantive and statistically representative evidence that supports Go/NO GO decision.
Here is an example of a process that is using the Opinion Miner software to quantify qualitative information needed for the analysis. Our methodology is focused on target customer experience AND on customer perspective - not functions and features of products. Instead of assuming the keywords that are relevant to the product or the company, we extract and organize attributes of customer experience based on what is important to the customers. Here is a 2 minute video that explains these concepts a little further.
The first step is to identify the boundaries that define the market segment we target. It is critical to remember that we interpret target market not demographically, or as a set of products we view as competitors, but a set of products that current customers view as "applicants" for their "job". For example if you are in the Project Management Software business you probably can think of a few competitive products, based on technology, or price level, or delivery such as SaaSvson-premise. Those are important, but not for this step. Now you should think like a customer who needs a tool to plan and manage a Small to Medium Construction job or a Public Relations consultant Engagement. What are the tools have they traditionally used to do that? You may come up with a seemingly unrelated set of products, however if this set of 3-6 products that are most popular, in other words successful with this segment of target customers, you got the right list for this analysis. If you are planning a next version of your own product, do not hesitate to include the current version into this list. There are no hard and fast rules of how many products should be on this list, but if you want to include more than 6, the likelihood is you did not work hard enough to define the customer "job" well. Instead, you are trying to “boil the ocean”. That activity may be useful for other tasks, but our methodology advocates more focused approach.
The next challenge is to acquire the "ore" for our mining. Some Consumer products and services are blessed by an abundance of customer feedback available publically in the form of reviews, blog posts, forums and such. However many products have very little to offer as their customers did not choose to publish their experiences online. When it comes to B2B products that problem becomes even more acute. I have heard many opinions about bias, quality and authenticity of unsolicited customer feedback online. Some people think that such feedback is almost exclusively negative as consumers use them only to rant about their bad experience. Some people think that such feedback is almost exclusively positive as consumers usethem to pat themselves on the back for making a wise decision to purchase great products. Then there is another group of people who think that all this feedback is originated not by customers, but by unscrupulous marketers. All of these opinions are very strong, but not very accurate. Over the years we have mined millions of customer reviews. The sentiment distribution pattern is similar to a standard bell curve. The authenticity is also not as major of a challenge as some people think. The practice of planting fake reviews is a very high risk/low reward proposition. Some companies have learned this at the expense of their reputation. Two years ago the law was passed to penalize such practices. Before this law came into effect we started developing some algorithms to spot and filter out suspected fakes, but since that time we had observed a substantial decline in planting activities.There are other, private sources of customer feedback that can be used for the analysis. I am referring to company forums, customer service tickets, sales notes, email/chat communications with customers, and even survey comments. If all or any of it can be had in textual form, it can provide you with the ore we need. We have also managed to use the survey mechanism to facilitate commentary. In other words we have asked only very open ended questions and did not ask to rate anything special. Admittedly it is not an ideal approach, but it is often the only available one for B2B customer feedback.
Now we are ready for extracting Customer Intelligence from the acquired feedback content. We use the Opinion Miner software that is capable to detect opinions that are emotionally charged. We treat them as "signals" and call them Attributes of Customer Experience. These signals are measured, interpreted and organized automatically based on statistical and behavioral economics models. But more importantly - the results are ready within a few hours from the submission of the content, and their accuracy and meaningfulness is completely open to the audit as verbatim is exposed. We are not claiming 100% accuracy, but our rates are very good for practical use.
The next step is identification of Attributes that can provide us with critical insights. If you are planning to disrupt a video game market in a Shoot-Them-Up segment, your game has to be not only better, but also different from the customers point of view, not yours. However since your game is still on the drawing board, you can learn what specific attributes of customer experience with current games are disappointing to their customers - People who paid money to buy these games. In this example "hit detection" experience appears to disappoint the customers of both leading competitors. Perhaps this presents an opportunity for differentiation and deserves a deeper look into the specific opinions.
A cursory look at the text of opinion’ snippets helps to validate the original finding. The numbers on the left side and the background color indicate that all of these opinions are Negative indeed. However we need to dive deeper into the content to understand WHY “hit detection” experience disappoints the customers.
I apologize for the low quality of the image. HTML does not transfer well into images. At least I did not figure out yet how to do it right.The Deep Dive requires actual reading and understanding what specifically caused a customer unhappiness, but by now you have only a small fraction of the original volume to deal with. In this particular example we have started with over 3,000 pieces of Customer Generated content, and within a very short time zeroed in on 3 opportunities for differentiation:Hit DetectionReliability and Customer supportThe Science stage of the process is behind us. Now it is a time for your Art. Your unique qualifications, your knowledge of the marketplace, of your company and you vision will help you interpret the found insights into successful product requirements.
Now is the time to ask yourself if your proposed product can improve customer experience based on the insights you have discovered in the previous steps. Can your proposed product eliminate steps or simplify the customer’s journey to obtain the Desired Outcome? Can your proposed product become an irresistible “applicant” for the customer’s “job”? If the answer is ‘No, but…’ it the best to consider abandoning this particular idea. What you have learned to get to this point will help you to ideate much better subsequent proposals.
I wanted to test our approach on some historical data and to share the findings with you.Once upon the time, before the first iPod was introduced, people used to buy MP3 players. Here is a disclaimer – I am not an Apple fun boy. I have never purchased an Apple product for my own personal consumption. However I am a huge admirer and a student of their Product Marketing planning process.For the purpose of this case study we have gathered 34,657 customer reviews for leading MP3 player models of that time. We have combined a few similar models of the same brand into a single group to get a larger data sample. The extracted Customer Intelligence exposed two major potential Opportunities for disruption.One of the most important attributes of the customers’ experience is Music Quality as almost 15% of all opinions expressed are about this attribute. And yet, none of the current products could meet their customers expectations.Secondly, all attributes associated with the user interface and navigation also disappointed their customers.When we encounter high importance and low satisfaction together, we are presented with a precious opportunity for innovation.
The User Interface, Usability and Navigation verbatim analysis finds customer comments like “awful navigation system full of menu choices” or “I have to stop jogging to sort through the menus and loose my rhythm. Very annoying”. Customers were begging for a process that allows them to enjoy music with minimum interruption. They wanted simplicity.
The music quality verbatim analysis exposed the fact that the customers’ primary source of content is low quality downloads and rip-off of the music from their own media. The proverbial “Garbage in-garbage out” expression is not limited exclusively to describe business applications. It is not possible to deliver a high quality reproduction of low quality content.It was interesting to sift through the verbatim – not a single comment was using such words as content or any similar word. That is where the art of interpretation and empathy with customer can create the simplicity of experience. Apple understood that the content eco-system was the key to portable music market domination. iTune’s eco-system expanded well beyond music, and now is the key for the portable content consumption market we call the Tablet. And yet, everybody else, except Amazon, still peddles devices.
This is the end of my presentation and now we open for questions.
Deciding what not to do
Deciding What Not to DoData Driven approach to GO/NO GO decision process