The positive effects of Word of Mouth references in customer acquisition (btw I hate that term) are very well documented.  Often I see the term “peer to peer” marketing being used in the same context interchangeably, however not being a marketing professional I am not sure if there is a difference or if they are really synonymous. Wikipedia defines WoM Marketing as

Word-of-mouth marketing, which encompasses a variety of subcategories, including buzz, blog, viral, grassroots, cause influencers and social media marketing, as well as ambassador programs, work with consumer-generated media and more, can be highly valued by product marketers. Because of the personal nature of the communications between individuals, it is believed that product information communicated in this way has an added layer of credibility. Research points to individuals being more inclined to believe WOMM than more formal forms of promotion methods; the receiver of word-of-mouth referrals tends to believe that the communicator is speaking honestly and is unlikely to have an ulterior motive (i.e. they are not receiving an incentive for their referrals).^[2]

Customer Reviews, describing personal experiences, opinions and recommendations of individual customers, are one of the best examples of WOMM. Amazon pioneered the approach and now there are many retailers like NewEgg, Best Buy and others, with technologies from BazaarVoice and PowerReviews that collect, manage and publish Customer Reviews.  I have both contributed and used them as guidance for my purchases for many years, and even though I understand that the reviews sometimes tell more about the reviewer than the product reviewed, I still find them the best tool for reduction of purchasing decision uncertainty. I know some tech pros and gadget mavens, who’s advice is sought and respected by many, to use customer reviews as an important part of their product evaluation process.

Consumers have no squabbles over paying for independent advice and recommendation, often called unbiased which is incorrect as such a thing does not exist IMHO. The Consumer Report was a very successful example and provided great service to generations of shoppers who subscribed to their magazine and its online version, however their model has difficulties to cover an ever expanding breadth of the products offered, and it does not really deal with customer experiences. The point however is that their approach is not misleading – you, the customer, pay them to learn their opinion and recommendation and thus the only incentive is to provide you with good and honest information.

I want to make very clear that I am not attacking profit motives or the marketing profession. I love profits when they are honestly earned by providing quality customer experiences, and I love marketing that helps me find providers of such experiences. The problems arise when some people or companies decide to focus on deception instead. Many years ago, one of my good friends shared with me her great admiration for Amway products. I was very grateful for her zeal to “help” me find a good product, until I realized the concealed motivation. Needless to say, we are no longer good friends, just acquaintances and I would never buy anything associated with the Amway brand. That is not to say that Word Of Mouth Marketing cannot be incentivised, just that marketers have to understand that it could become a double-edged sword and can easily create unintended adverse consequences. It also creates a challenge for us, at Amplified Analytics, to develop an effective approach to weigh authenticity of reviews we analyze for producing Product Reputation metrics.

We continue to test and debug the PRMIR (Product Reputation Market Intelligence Reporter), to get it ready for private beta. Original scenarios were focused on use of the Product Reputation data by product marketing managers of Consumer Electronics manufacturers to spot “systemic” failures of the products they are responsible for, and provide them with information to assist in developing corrective actions. However as I test the PRMIR, I keep coming up with new ways to focus and filter the information from different perspectives. The consumer focus (i.e. “what is the most reputable 40″ flat screen HDTV?”) is the most obvious example.

Best 40 inch TV

All 30 of very popular Asus netbooks have very high reputation for their functionality and design, but over half of them have some support problems. If I was responsible for Asus technical support or Customer Experience management, I would surely want to look at the source of that information (verbatim). The problem is that these metrics are based on 4,882 customer reviews and any meaningful analysis would take a significant amount of time to locate specific references to the support issues.  The Support “filter” below helps to focus on the subject of investigation.

Asus Support Filter

Click on the image to enlarge.

I found an interesting post by Jeffrey Henning today. The article is touching on emotional attachment people have for different measurement  scales used in Market Research. I can see how easily it come into play as we try to find one method to fit variety of research projects. Every method or tool has it’s limitations and therefore the challenge is to find the most appropriate one for the task at hand. Jeffrey quotes Brad Borther who provides an excellent advise:

Ten-point scale: “A five-point scale is totally inappropriate for customer satisfaction studies. Why? It lacks enough granularity and robs companies of a burning desire to take corrective action. It commonly leads executives to believe that ‘80% rate us four or five; that’s great, let’s move on,’ without realizing that it simply means that 80% are at least somewhat satisfied. Further, many people will never rate anything a ‘five,’ resulting in ‘four’ including those who are really very satisfied and those who are only somewhat satisfied. To avoid this topping effect, use at least a 10-point scale and count nine and 10 ratings as fully satisfied. This will also allow easier analysis of what bottom-line effects satisfaction has, since such tools as regressions work better with a more granular score.” – Brad Bortner, principal analyst with Forrester Research, “Best Practices: Why Customer Satisfaction Studies Fail“

Since our approach to measuring Product Reputation (delta between Customer Expectations and Customer Experience) is focused on competitive position of multiple products within their category, and our method does not require to ask people to measure it,  I have decided to use “0″ to “2″ balanced scale with 2 decimal points for more granularity. It is interesting how infrequently people want to challenge a value of our methodology or accuracy of our analysis, compared to the selection of the measuring scale. By now I gave up any attempts to change their mind. We arrive to the scores using our algorithms to analyze Customer comments and reviews, not by asking them to measure according to any scale, therefore is much easier for us to recalculate Product Reputation scores to appear in a customer “favorite” scale. The integrity of the finding is not compromised by the conversion.

I wish all religious wars could be settled that easily.

I wrote this story awhile ago, before we had this blog started, to eventually publish here.

It all started in August 2007, when I had to travel across the continent almost every week and started shopping for a lightweight laptop computer suitable for business travel.

While selecting parameters for my planned purchase in terms of specifications was not too difficult, if you know what you want, predicting the quality of your ownership experience may prove to be much more complicated. I’ve been an online shopper for a long time, but the recent cost of shipping and the hassle of dealing with less and less responsive customer service reps, started to outweigh the original savings and conveniences.  As a result I became much less impulsive with my online purchases – in this economy there is less money to spend and less time to waste, so I figured a small investment into initial research would be a good thing.

I found three major sources of information that were quite useful to assist me in making the choice:

1. Product specifications provided by the Original Equipment Manufacturer that are part of advertising and marketing collateral and designed to create our expectations of functionality and performance, but provide little help to gauge the probability of these expectations being met;
2. Editorial Reviews provided by magazine and online publishers that offer us a glimpse of potential user experiences which are quite valuable, but substantially removed from the regular consumer environment – the editors test carefully selected and tuned equipment provided at no cost to them by the OEM, and don’t have to deal with fulfillment, delivery and customer service issues. Unfortunately Consumers Reports did not review the laptops I was interested in and their recommendations were not available. A relatively quick tour of a few popular web sites helped me to create a short list of the two laptops that met my requirements;
3. Consumers (Users’) Reviews provided by actual purchasers of the product who share their personal experience and rate their satisfaction with this product. There is a relatively high probability that one will be very satisfied with a product that has been rated very highly by most reviewers. Adversely, you will do well avoiding products that are rated very low by most reviewers.

Two laptops that I had short-listed for purchase, based on product specifications and editorial reviews, had very similar reputation ratings of 3.5 stars out of 5, which is not perfect, but acceptable. So what is the next step? Toss a coin? Is it safe to assume that these two products have the same reputation and would be equally satisfying purchases?

It turns out that this would have been a very bad assumption.

Usually I lack in patience (those who know me, please stop laughing – “Good men know their limitations”), but this time I decided to assess whether the reasons, that prevented these laptop users from giving the highest satisfaction ratings of 5, are “showstoppers” for me, or not – we all have our own limits of tolerance to different experiences. I ended hunting for and reading through dozens, or sometimes hundreds of reviews and found out that the most negative experiences with laptop #1 were centered around overheating issues and resulting customer service hassles, where negative reports of laptop #2 were focused on order processing and fulfillment problems.

I had invested 8-10 hours of my time in research and spent $120 more than originally anticipated, to purchase the laptop #2 from an online retailer that had it in inventory, to bypass the fulfillment problem and have been enjoying my laptop without any reliability problems. I hear the laptop #1 OEM has finally found workarounds for the overheating problems and is now working to pacify many of their very vocal and unhappy customers.

As smug as I am about this experience, the efforts required to do such research require too much time and patience and I wondered how much easier it would be to have more meaningful product reputation ratings. So I looked, but could not find anything unbiased, consistent and verifiable to make it work for me. That is how my new project, Amplified Analytics was born. Please look around the site and let me know if it makes any sense to you. I would love to hear your experiences related to product reputations and user reviews.

Very interesting results of the survey:

A Social Media Survey conducted on behalf of PRWeek and MS&L by PRWeek and CA Walker found that marketers don’t make changes to their products based on customer feedback, despite monitoring feedback being one of the most common business uses of social media in the first place.

The survey found that 70% of marketers say they’ve never made a change to a product or marketing efforts based on feedback from consumers on social media sites.

I have to second Larry Malloy’s comment.

I believe there’s two reasons for this.First, we are still in the early stages of social media as a marketing tool. I believe as the technology matures, potentials are stretched, metrics are determined, and processes are developed this will change.

Second, there could be a disconnect between marketing and product management (you said the survey polled senior level marketers). As a product manager, I often used social media throughout the product lifecycle, and the executives I reported to often did not know where the new product ideas came from. And, what I learned through social media, I often further tested through more traditional marketing technologies like surveys, customer visits, interviews, etc.

Most Product Management and Marketing executives I have talked to are interested in listening, but have no strategy, processes, methodologies or best practices to act on customer feedback. Most tools available today are not providing particularly actionable data either. I am not sure what would or should come first, but without these elements you cannot produce any ROI. I attempted to come up with a “calculator” to measure an impact of customer feedback on product profitability, but it is just a rudimentary attempt for discussion and anybody who wants a copy can find it here.

I read a very interesting post on the Wikinomics blog today called “A future vision of CRM”

I’ve heard the argument that traditional CRM “is dead,” but this is far from the truth. In fact, as Brian notes, Social CRM does not replace transactional CRM systems, rather it augments them. What CRM is in desperate need of is new data sources and tools that help integrate and analyze this data. The future vision of CRM also requires that companies get involved in new channels and cede a certain amount of control to the customer – it’s less about management and more about engagement.

and left a comment I hope you find interesting:

One of the challenges for Social Media channels and CRM integration, is the fact that they “speak” different languages – SM is mostly communicates in unstructured text, while CRM is using formalized data structures.

There is a potential for tremendous benefits and cost savings for Marketing, but scalability, transformation of data into knowledge, and new processes for translating this knowledge into measurable actions, still need to take place.
Your examples of corporations adopting SM channels, while sexy and newsworthy, may prove to be uneconomical in the long run as a Customer Service operation mechanism, unless the automation of these processes and work-flows, can be automated.

Let me know if you agree.