It seems that the major difference between product management practices in the software business and the consumer electronics business lies in the perception of how, or even whether, a life cycle of a product can be managed after its release.
In software, alpha and beta testing by actual users are a common practice, that results in multiple releases based on actual user experiences learned or observed during these processes. In other words the product is actively managed throughout its life-cycle.
In contrast CE product management practices do not appear to be very pro-active after product launch, and are limited primarily to promotional functions. If a product is expected to have an 18-24 month life, focus groups are organized 12-14 months after product launch, to learn how to design and market its next generation. These exercises are very expensive in that they require a lot of effort to organize, and a lot of special skills to produce truly valuable results, hence they are often contracted to specialists.
Most intelligence a company can gain about its customers’ experiences is by listening to its customers, literally. While customer satisfaction surveys are valuable, they are typically post-dated from the original experience and only solicit feedback based on topics the company deems important.
There are multiple channels available for finding this data, and multiple technology offerings to process it into a meaningful source of business intelligence, however I am not aware of many processes that use this intelligence to pro-actively manage launched CE products profitability.
At Samsung, using reviews as a source of feedback “has changed some aspects of the way we work, primarily because of the speed with which information comes in”, says Kris Narayanan, Samsung’s director of marketing. “It helps us look at issues as they arise. If there is a malfunction or a problem, then we identify it very early.”
The company has used reviews in this way for less than a year, but Narayanan says Samsung has already changed products in response to the new kind of feedback. For instance, large flat-panel televisions were initially produced with speakers on the side. When customers pointed out in their reviews that the units were too wide to fit into conventional cabinets, Samsung put the speakers below the screen.
The example above is a very positive one, but keep in mind it only addresses the issue of the “next” product design – not how to improve profitability of the “current” product. However I suggest that it can be done and I would love to learn about people and companies who are already do, before starting to speculate how I would approach doing it myself.
As usual, your comments, opinions and experiences are greatly appreciated.
I’ve been following a good number of discussions, on blogs and Twitter, about ROI in Social Media. While many of them are debating issues of advertising, public relations and marketing, the most interesting to me are those of Social CRM, or extension of CRM functionality into Social Media.
Within that area, I find the most exciting discussions to be those surrounding Customer Loyalty value, because it is so hard to define and to measure. While some CRM thought leaders, like Esteban Kolsky (@ekolsky) have flat-out declared that Customer Loyalty does not exist, others, like Kevin Stirtz of the AmazingServiceGuy.com attempt to come with methodology to estimate it.
Customer Loyalty Value Calculator does not provide ultimate answer for every business, but it does identify factors and logic that allows to illustrate the impact customer loyalty makes on bottom line.
“For any business, Top line is vanity, Bottom line is sanity, Cash flow is reality”
Product Reputation is another term which is difficult to define, measure and manage. It is often misunderstood as measure of Customer Satisfaction with a product, and both are certainly related, however the methodologies around measuring them are quite different and that makes measure such as CSI (Customer Satisfaction Index) or NPS (Net Promoter Score) results not as actionable, in my opinion, as Product Reputation scores. However all of these do, arguably, influence financial results, and overall brand value of the associated products.
I define a Brand Reputation as an aggregation of Reputations, Products associated with the Brand, enjoy with their Customers. Deterioration of Product Reputation can eventually erode the value of the Brand. We see Product Reputation as the delta between customer expectations and actual experiences, and this delta can be measured using semantic analysis technics.
Inspired by Kevin, I decided to build a similar simple calculator, which I called Product Reputation Impact calculator.
While it is a simplistic and rudimentary model, but it is useful for understanding how even small declines in the Product Reputation can result in sizable financial shortfall. The good news is that it also shows that there are opportunities to defend your Product Reputation, if you know what is (are) the cause(s) of the problem. In the above example the Product Functionality Reputation is under pressure and Customer Feedback verbatim analysis may indicate that modification of the marketing messages, that are creating these inflated expectations, can easily be adjusted to bring the Product Reputation into balance.
I would love to receive your feedback about this approach and if you would like to take a closer look at the Calculator, I will happily send you this spreadsheet.
A couple of years ago I had an experience that eventually led me to start Amplified Analytics, the company that developed technology to find customer reviews and to translate them into Product Reputation metrics. We decided to focus on Consumer Electronics and Computer industries’s products, and concentrate on voice of the customer, rather than “noise” of social media in general, to produce truly actionable “signals”.
We employ proprietary*, multi-dimensional semantic analysis of customer generated content to convert explicit and implicit sentiments found in free-format text, into specific and actionable metrics. We keep the metrics objective and unbiased by:
- Depending solely on consumer reviews about any and all products we rate
- Excluding any and all manufacturer sponsored editorial reviews
- Not depending on advertising support
- Filtering out duplicate reviews even if they are found on multiple sites
We are now ready to field test our first product V2P Accelerator that is designed to dramatically increase visit to purchase conversion rate for e-commerce sites, and looking for a innovative retailer who would weigh potential growth in revenue over the risks of partnering with a start-up. Please contact me if you are interested.
I’m trying to get us selected as a finalist for a Juice Pitcher competition that will be held at the Microsoft Campus in Mountain View on October 6th.
We’ve created a company profile on Vator’s website .
What I need you to do is vote for us. Please go to this page and vote for Amplified Analytics Inc. The final day to cast a vote is September 29, please do not delay.
Thank you for your support.
A blog about experiences, curiosity and the never-ending search for ways to do better things better