The CES2010 aftermath

I took almost a month to recover from my CES2010 and now I can attempt to write something more or less cohesive. The experience was absolutely overwhelming. Bright images on gigantic screens and loud sounds continuously blasting away are to be expected at Consumer Electronics trade show, but my mind could not function very well in these conditions.  I have not visited such large, noisy and heavily attended events for a few years and the assault on my senses was very difficult to bear, but I managed.

We are a new associate member of the Consumer Electronics Association and this was my very first visit to this event. CEA offers a terrific Mentoring program to its members and I came to Las Vegas to take advantage of it. It is amazing how much one can learn from truly knowledgeable and generous people even during a short personal meeting. I am very grateful to Bill Matthies of Coyote Insight for sharing his deep knowledge and understanding of the marketplace. I started this company with an idea of converting virgin data into actionable information, and we have almost succeeded – Bill made me realize that the link between our metrics and an action is very obvious to nobody but me, and advised to share that link with others using “stories” and “pictures” like this:

PRMIR – Deviation of Reliability Reputation scores for the Docking Station Product Category

Robert Heiblim of BlueSalve and my CEA Mentor, helped me understand the inter-workings of the CE community better and to meet people in CE product marketing to learn more about how they go about conducting their business. I only wish I could get more of Robert’s guidance and advice.

I need more examples of business processes where product managers have to “translate” data into “information” that suggest action.

Consider the actions a marketing product manager can take based on the data that their product ABC has a low satisfaction score. I can’t think of any other action than to learn more, i.e. to discover more data. Presumably information is created when our marketing product manager (or product marketing manager) compares ABC’s product satisfaction score with the one of a competing product, hence comparison of two points produce information, i.e. higher value.

Correlating the information produced by tracking these two data points over time with sales numbers can create knowledge – “product with an inferior reputation tends to undersell its competition by X%, when sold at competitive (i.e. similar) price”. Now, this is an actionable piece of knowledge as our MP/PM manager can attempt to discount the ABC product to stimulate sales or attempt to improve the customer’s opinion about it.

Can you suggest any scenarios where aggregated customer feedback about reliability of a product XYZ can lead to/suggest an action that protects and/or improves its profit margin? Your help will be deeply appreciated.

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2 Responses to The CES2010 aftermath

  1. Alex Tanner says:

    I wonder how much Customer Service data there is in the reviews you analyze. Most people probably write about extremely good or extremely bad experiences. Is there enough “meat” in these reviews to be of any use to a Tech Support organization?

  2. Gregory says:

    Alex,

    Thank you for your interest. I would say we are getting no more than 10% of customer reviews per product that implicitly or explicitly describe their support experience. Popular products with a large number of reviews provide sufficient (statistically representative)information for analysis. It also a constructive practice to bundle reviews for products from the same company/organization (ex. Samsung TV’s) as they often are supported by the same part of Customer Services and provide very good window into the operations. I’ll follow this response with some illustration how customer feedback about support (the PSS-Product Support Score)can be analyzed using PRMIR to generate ideas for improvements. Let me find some examples from our data base.

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