How to Turn Knowledge into Data: Customer Reviews


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We are constantly pressed to do more with less, or to become better at producing more of the things that get us greater results.

We want to spend more of our time doing things that work and less on failing. To do that, we need to become more of what we are. Because of our biases and assumptions, we learn more from the feedback we receive from others. Which takes some parsing, as others are also focused on self.

Our methods should helps us experiment and iterate to build momentum. This is preferable to testing, although that is valuable downstream, after the iteration, to optimize where we net out. The first is about expanding options by enlarging our horizon, the second involves picking one among the options we have. Starting with the first is a good idea. But how?

The other side of the problem is that there is only so much information we can retain and use on short notice. Which is why some of the smartest people continue to bet on building their capacity to become more effective at what they do by thinking better. “Measure twice, cut once,” say wise carpenters.

With customers, and increasingly prospects, we don't get a second chance to make a first impression. All too often we have no idea of why we missed the mark. With enough products and services ready to do any one job, the emphasis has shifted squarely to the realm of experience. A fuzzy area to control.

While it's hard to predict the qualities of the next hit campaign, product, or hot news item, it is easier than ever to learn what people think about a certain type of service and what's missing or appreciated in existing products. The information is everywhere, and especially in reviews and conversations.

For all the recent talk about consumer generated content and customer-centric businesses, the opportunity for companies to learn and gain insights is still wide open.

How to turn knowledge into data

Reading reviews and conversations online is like going to the school of life. If we only pay attention to the keywords and numbers, we may miss the whole point —the experience. Why do people say what they say? How do we draw insights from disparate comments? Is it possible to separate a fad from a trend?

There is a lot of human data in conversations, starting with the questions people ask. How to listen is the most valuable skill that nobody teaches. Insights require imagination and creativity, and while we can automate and optimize a lot using modern tools, we expand our options when we include good decisions in the mix.

To do that we use the view from somewhere. Some examples of what it takes to develop it include:

  • research and deep insight into the operational and/or organizational reality of a specific challenge customers face
  • a novel approach or method to address the challenge, including making the case to address potential objections on shortcomings
  • examples of coherent applications of the proposed method to high-stakes situations corroborated by facts and solid logic

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In a webinar for Target Marketing this week, I provided some ideas on how to turn knowledge into data by parsing information in customer reviews, conversations, and comments. You can find my deck below, and listen to the full recording of the webcast on demand, which includes tons of data from BazaarVoice and a success story about Rubbermaid.

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There are many good reasons to listen to what others are saying. Online, companies can learn about product ideas, what their competitors are doing, how service differentiates them, and what makes a great experience.

While organizations worry about their brands and business, as people we think about our credibility and reputation. Take for example wines. The most common questions we have are about wanting to have a great experience and not look bad —how do I figure out which wines to buy for different occasions? How can I discover new wines? Wines like the ones I enjoyed?

Questions about wines

Experts build a reputation so they can make recommendations on our behalf —do it for me. Apps like Delectable and Vivino help us find wines based on ratings, save them, upload our own preferences and return data about us to us —do it for us plus do it for myself. As marketers and tool builders, we can provide value based on what people are trying to do —find new wines, match the occasion to the vintage, figure out what is similar — and in turn generate value for the business.

Help make people's lives easier

Then there is a third option —that of upgrading the customer. Teaching people how to learn about their own taste by demystifying the process, and helping people have fun while they are getting smarter. Humor helps people feel connected —they say laughter is the shortest distance between two people. By upgrading the customer we earn preference because we have permission to interact.

Our customers have more sources of information than ever before, but so do we. We can choose to address issues and learn from the experiences of other companies and brands as well. The very tools that empower buyers can become a source of additional information for us —on behavior. Which creates more options for marketers to display information that helps customers make choices better.

In other words —connection is a two-way opportunity. For example, when we think of it as a service, we can help people see what people like them are doing, eliminate unnecessary steps between people and what they want to do, and making it easier to do things.

Consciously and/or unconsciously we use decisions as a way to show and confirm to ourselves who we are. And our identity is connected with our behaviors, but our answers depend on context. By now we mostly understand that there is a trade-off between being connected, staying informed and our privacy. but that trade-off comes with strings attached —we expect more from organizations and brands.

People bring their whole selves to experiences, and their tribes as well. Marketers are familiar with the concept of persona —who she is, what she does, and so on. We use these stories to ground our work into real people with observations of what they actually do rather than just what they say.

But how can we figure out what they actually want? What's in their heads? It starts with our thinking —we need to take into account the larger context of their lives. When we start with why, we can figure out “what” and help with “how.”

Our point of view is still very much business-centric, even when we talk up customer-centric  —when we say “world-class customer service,” for example, as companies we mean “world-class service,” while customers want “world-class customer.” How do we make them and their lives better? That elicits the best kind of consumer generated content available.

Word of Obvious

We won’t get there by misbehaving —we need to learn to go beyond the stars, and learn to translate emotion transmitted via words into data (what we call human data). The Amazon algorithm is still learning. But as people, we can learn faster, if we want to —from each other.

Organizations look at people as new forms of media, so when they see a great article about a competitor's product march to their agency, “I want some of that.” When we shift the focus from the article or media coverage to the underlying qualities of the story we can make more headway than just trying to buy “influencers.”

How some organizations and brands get to “word of obvious” is still not sinking in —we need to change our approach. Are we still having relationships locked inside our CRM system while trying to operate in a networked marketplace? Relationships are much more important than transactions to people, and now they have the tools to demonstrate it.

Which is why when brands don't walk the talk, talk is cheap; why surveys are still about the brand while reviews are about experiences —who and what would we rather talk about? How quickly can we get to that composer box to have our say?

Customer Company interactions

Amazon didn’t invent people, they just make it easier for existing behavior to manifest itself. Sites that enable product reviews sell more, gather better product feedback and higher credibility. Because the data is right there —in the reviews. “Not quite” means I can learn something (and there is a give and take with a product guarantee, so people will more likely help that brand.)

Reputation is earned. Service is still special in social for two main reasons: 1./ a clean slate for companies, 2./ smart brands get that everyone is watching. Which is why people do post to social networks when they struck out in regular channels or are frustrated enough.

People are more than capable of filtering the noise. But are brands flexible? For example, the star rating cannot be changed on Amazon when updating the review, it requires entering a new review. A technical issue that could impact the reputation of an author or brand —what is the Amazon’s incentive to fix it?

Even in the comments to media sites —notoriously a very challenging place— people can tell extreme positions and substance free comments, as Ars Technica demonstrated in a study that identified the language patterns in bad comments.

Retaliating for negative reviews is not a good idea. How far does it get us when we do this kind of thing to another person? The best way to go about that is to reflect on the underlying behavior and provide incentive to do the right thing, instead.

Most of the problems we can spot is reviews are about (not) keeping promises. One obvious place were we can spot the issue is in peer marketplaces like Kickstarter. We can learn what are the words that work to fund projects, for example. Studying patterns in peer marketplaces are also a great way to uncover which products work and to understand the importance of building an audience first.

Words that work

But then we have to deliver, or people will tell each other where else you can go for a similar item. We're helpful that way, social animals. We can try the shortcuts, or we can take a longer view, which still leaves plenty of room to build relationships the right way and grow a company's business.

When we give people credit and go the extra mile to help them get to why something matters, the proverbial “so what,” they/we come through. John Oliver demonstrates how influence is a side effect of interestingness.

“Any new technology, any extension or amplification of human faculties when given material embodiment, tends to create a new environment.”

[Marshall McLuhan]

Every technical innovation creates a new environment that alters the inner image or identity of entire cultures. To go beyond the stars, we need to learn to go beyond the product or service to the larger context of work and life. This is how we should build experiences, so we can upgrade the customer, which is what she/he wants. By converging message and service we can bypass the competition altogether.

But relevance is about give (first) and take.

Here's the full deck of my presentation.

How to Turn Knowledge into Data: Customer Reviews from Valeria Maltoni

To listen to the full recording of the webcast on demand go here, it includes tons of data from BazaarVoice, success story about Rubbermaid, and the Q&A with participants in  listening mode during the webcast.


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