Differentiation and Customer Intelligence

 

One of the interesting challenges Marketers are charged with is to make their product or service stand out in minds of the potential customers. Those who are not blessed with analytical talents commonly slide into well bitten path to differentiate by specifications or price. These approaches do not really require any expense and/or curiosity to seek deep understanding of the customers, but they are ultimately led to erosion of profit margins and brand equity. If you, brand “owner,” don’t care about the customers, the customers don’t care about your brand. Advertising alone could carry the brands a great distance in the “good, old days” but in the age of Social Customer, an advertising message is expected to resonate with customer needs or it will cause more harm to the brand image and product sales than good. When it comes to a product reputation or brand equity, the notion that “Any publicity is good publicity” is not the best strategy.

None of it is new to most marketers and some companies are spending serious money to develop processes for discovery of consumer/customer insights. However, most are struggling to convert the findings into specific actions. Measuring financial impact of these actions seems to be an even more formidable challenge. I would like to explore these challenges and perhaps offer some ideas for dealing with them.

Many marketers today are too insulated from their customers to develop a true, genuine understanding and empathy of customer experience with the products or services they market. One of the reasons is the use of outdated market segmentation methodologies based on demographic data that was developed to help marketers to quantify and forecast, but do not provide much help in understanding the needs and discovering opportunities for differentiation. More evolved methodologies that attempt to develop customer “personas” are much more helpful in learning needs of the specific, pre-defined groups of customers. Scott Sehlhorst of Tyner Blain offered a wonderful explanation of how such methodology can be used.

Use of both abovementioned approaches together will likely to improve your product traction, but will fall short of true understanding you need to differentiate your product because everything you have learned so far is based on your own original assumptions. You start with a hypothesis of who your potential customers are, what functions and features they would like in your product, and how much they will pay for it. Then you proceed with a number of potential customers’ validation and advisory activities that confirmed or cancelled your assumptions with various degrees of certainty. However, you still don’t know if the group and personas (within the group) are your best potential customers since you cannot possibly validate that with every potential segment. Additionally, I don’t think it is possible to effectively differentiate – by design, packaging or message – without ultimate understanding how the customers experience the product. All the steps you have taken so far cannot give you this knowledge for 2 reasons:

  • You have started at the “wrong” place – i.e., demographic segmentation of market is a wrong starting point. Much better starting question is – what products/services my future best customers are hiring today to do the job they need done. I use here terminology and concepts developed by Clayton Christensen. Check this video where he explains why the basic thinking taught in business schools and promulgated by consultants is killing innovation and the US economy if you are not familiar with his work.
  •  Any knowledge of customer preference you have gained so far is company-biased because it was obtained by methods of inquiry and/or moderation. The one who forms a question or selects the subject of discussion ultimately influences any possible outcome. I do not believe that there is such a thing as an unbiased research, and I prefer customer’s bias to a company’s bias for the purpose of learning how a customer experiences a product or a service. This is my preference because regardless of our opinion, that is what they are going to use while selecting to purchase your product or a product of your competitor.

I am not dismissing the value of traditional methodologies off hand, but I am suggesting that substantially better results can be achieved by using triangulation of these with true insights of customer experience. There are plenty of customer-generated content available online for aggregation and analysis; however, even if you find difficult to find good data, we had very good results by asking customers wide open questions designed not for validation and easy tabulations, but to help them tell their stories:

What made you interested in a product XYZ?

  • How and where do you use it?
  • What was your experience so far?

 

Let them know that you asking because you want to learn how to make their experience better and promise that you will let them know the results of the study. Most people are motivated and willing to help. These types of questions are traditionally reserved for qualitative research that in the past was considered expensive, and the results are often dismissed as statistically not representative as they are normally reserved for a small number of customers. Those who try to find insights manually in large volumes of data are quickly get overwhelmed by “drinking from a fire hose.” However, advances in opinion mining technologies significantly reduced cost of high volume content analysis and can offer benefits of qualitative research and statistically representative numbers to back up the value of insights. In the words of Clay Shirky, “There is no information overflow-it is a filter failure.”

Good use of right technology can provide a marketer with a substantial and representative number of clues and hints to how customers think and feel about their experience with a given product or a group of products. However, no automation or outsourcing can replace your creative power of interpreting these clues into actionable insight. You can see examples regularly published on our Google+ feed.

The language customers who used to describe their experience will also provide the source of how to communicate with the market in the way the message will resonate and connect on the emotional level.

 

 

 

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