If you are interested in engaging your customers, your listening has to be customer-centric. I know you want to talk about your product and you company. We all want to talk about things that are important to us, but we only engage with people who listen at least as much as they talk.

Many marketers are intrigued with the idea of using Social Media in their go-to-market campaigns for the next product launch. They are disappointed to learn that there is usually not enough customer feedback available at the time of a launch to propel their new product to instant, viral success.

Authentic word of mouth cannot be “manufactured” by marketers when they need it, but can be leveraged very successfully when customers are engaged with their brand/category. Engaging customers is not an event within a campaign, but a long term, customer-centric strategy.

In the words of Brian Solis

The first mile of customer engagement is a post-commerce or post-transaction strategy that invests in an ongoing experience to keep customers happy now and over time. Doing so sparks positive word of mouth and in turn influences decisions the dynamic customer journey that defines the new era of connected consumerism. If in fact getting closer to customers is a key objective, then why do many businessesneglect the first mile of customer experience?”

Every product experience starts with an expectation. The expectation was originally initiated by product announcements, industry analysts interpretations of these announcements, pundits’ reviews and commentary, customers’ word of mouth, and eventually your own experience. When this experience exceeds the original expectation, the Social Customer has a propensity to generate authentic, positive word of mouth online that is read by scores of interested consumers, who view it as the most trusted source of information about your product.

Many companies monitor social media to supplement their Customer Support channels to help resolve specific customer issues. This is surely a part of Customer Experience, but only a part. Multiple and loud accolades to customer support satisfaction may spook potential buyers by making them think that the product quality is low, because it requires so much in terms of support efforts. However, customers’ stories describing why they have purchased the product and whether it met their expectations truly help potential buyers decide if this is a right selection for them.

The goal is to learn from a very large number of customers, in a very short time how they perceive your product and whether it has met their expectations. The techniques employed in the listening process can be used during go-to-market campaigns.

There is a lot written in the last few years about the importance of consumer engagement with brands in the age of  the Social Customer. Most writings are focused either on teaching how to get most Facebook likes and Twitter followers for your brand or how to manage PR disasters fueled by social media winds.

I always look for evidence of Social Customer impact on business growth. Intuitively, most people would agree that satisfied customers, who actively share their experience with other consumers, impact the product and brand market share growth. However, intuition is not very powerful agent of organizational transformation, I hope a proof in a form of data has better chance of success.

The most valuable insights often hide in the intersection of multiple data sources. For example, let’s look at how the combination of social media engagement and customer satisfaction information correlates to changes in a brand market share.

As smartphones represent one of the most dynamic and socially engaging market segments, it provides a good source of data for our example.  See below the percent market share by operating system for the first quarters of 2012 and 2013:

(Source: Kantar WorldPanel “Smartphone sales by operating system-U.S.” report)

Amplified Analytics online marketing research mines customer reviews to produce Social Customer Engagement and Customer Satisfaction scores. We intentionally used Social Customer data from preceding time periods to examine the influence of social feedback on customer behavior that produces market share change.

After combining the data from both sources we calculated the year-to-year change you see below.

The Windows example suggests that strong growth of Social Customer Engagement combined with robust improvement in Customer Satisfaction lead to very meaningful change in the Market Share.

If you are like me, you probably receive requests to share your opinion about websites, products or services on a daily basis. That is not surprising if you consider number of technology and service providers that claim to make VOC solicitation and collection cheap and easy for companies.

I often wondered why do they go to the effort and expense of soliciting our feedback while at the same time ignoring Word of Mouth that is shared online by their customers without any solicitation.

The other day I received an email survey request from the manufacturer of a vacuum cleaner we have purchased a few weeks prior. Very polite message from the Customer Experience Director intimated that their VOC program needs my feedback. I liked the product a lot and left a very favorable review on the retailer’s website describing my experience. In fact, a few people marked my review as “helpful”. So why this polite gentleman wants me to answer 32 questions about my satisfaction with their product?

Have I not already published my feedback under my name? I posed this question to the Customer Experience Director and suggested that the survey questions were convoluted, too wordy and focused on details of no importance to this customer. The response indicated that the company does not include Social Media feedback in their Customer Experience and Satisfaction measurement efforts because it is a domain of their Digital Marketing group and their Customer Service department’s Social Media listening team.

Fragmentation of corporate view of a customer and it’s negative impact on Customer Experience are well documented by experts and sadly experienced by many consumers.

Many companies are striving to engage with Social Customer. However, they insist on controlling method, level and form of engagement. It is not very smart and it will not work because Social Customer has alternative options. Corporate believe that social media research does not produce as valuable market intelligence as VOC is analogous to the conviction that bottled water is “better/cleaner/safer” than the tap water.

Social Media research of WOM has to be included into VOC programs because:

1. WOM often produces much larger data samples. Low customer survey response rates are always a subject of concern that results are not statistically representative.
2. Social Media research of WOM does not carry a risk of creating a negative touch point of customer experience by poor execution of VOC effort. Considerable skills and efforts are required to craft the survey questions and to administer the program without introducing friction into customer communication with a brand. WOM analysis helps to ask questions that are more relevant to customers.
3. The results of Customer Experience Management sponsored VOC measurements are not visible to the consumers and if there are, are not believed by the consumers who see it as a form of advertisement. VOC produce metrics, consumers communicate telling stories.

With the advent of Big Data, it is estimated that 70%-80% of all data collected and stored by an enterprise is in an unstructured form. There are various approaches, technologies and methods to automate the analysis of unstructured data such as text.

However, regardless of advances in technology, some Customer Experience Management, Marketing and Customer Service professionals continue to use the accuracy argument to deny their employers access to significant operational and financial benefits.  They argue that the results, produced by the textual analysis software products, are substantially less accurate than results produced by humans, and therefore it is best to ignore the vast repositories of human knowledge and disregard the immense cost of storing them until the technologies mature.

It is humorous that people with such attachment to “accuracy” usually have difficulty clearly defining what it means to them in this context or how to measure it.

“In the fields of science, engineering, industry, and statistics, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity’s actual (true) value. The precision of a measurement system, also called reproducibility or repeatability, is the degree to which repeated measurements under unchanged conditions show the same results”

Given the ambiguous nature of unstructured data, the challenges of formal definition are easy to understand. In its core we deal with an interpretation by a human or by a machine of what was said or written by another human. A single individual will interpret the same text with different results depending on a multitude of conditions, such as time of day, context in which the text is framed or the state of mind of the interpreter at that moment. In addition, no single individual can possibly handle the volumes of data available – and with each additional interpreter joining the task, the reproducibility of translation results declines exponentially.

The speed and cost are obvious arguments for the automated processing, but a machine also offers a better solution to the problem of the “accuracy” of big, unstructured data analysis.  An interpretation of a single piece of text may not agree with an interpretation of a detractor at a given moment, but an average result of a large data set analysis will consistently produce measurements within 10% of a human tester’s results*.

The debate isn’t whether or not automated analysis of unstructured data is “accurate” enough. The debate is whether an enterprise can ignore their vast data reserves in the Age of the Social Consumer.

* This number is based on our internal tests that we conduct at least 3 times per year.

Knowledge of customer satisfaction and experience delivered by a specific channel can be very illuminating from a brand manager’s perspective. It could be even more enlightening if customer satisfaction metrics also analyzed units sold by each channel and units returned. When these streams of data consistently correlate and/or trend together negatively, it is likely to indicate systemic channel performance problems.

From the channel perspective, customer satisfaction with specific brands – and even more importantly, with specific products – can help optimize shelf space for maximum profitability.

The detailed analysis of customer feedback (reviews) and customer support communications associated with a troubled channel or brand can provide root cause(s) and ideas for corrective actions.

Below is an example of a report on customer satisfaction with smartphones by channel/carrier. The information was mined from 142,369 online customer reviews published prior to March 30, 2013. AT&T customers who use Nokia smartphones reported customer satisfaction 21% above average across all major carriers* and all major brands.

* Sprint did not offer Nokia smartphones during the reported period.

Deeper analysis may reveal customer satisfaction by model, time period, customer gender, age group, other personal characteristic, or geographic region. Please contact us to discuss methodology for mining intelligence in your market segment.

This is our third annual analysis of customer perceptions of smartphones. This report is produced entirely by means of Social Media research. Customers became even more active in 2012, sharing their experiences with products they chose for the benefit of consumers who are shopping for smartphones.

Source: cmsoforum.mckinsey.com

The last year saw an increase in unsolicited Social Customer engagements with brands in this category of over 75% — from 29,971 in 2011 to 52,517 in 2012. The quarterly trends indicate that the rate of engagement is still accelerating. The following filters were applied to arrive to these numbers:

• smartphone models that have at least 100 customer reviews published on multiple SM sites
• content is unsolicited and volunteered by actual customers
• content was published on or before 12/31/2012

We produce smartphone market reports to illustrate the power of our technology developed for DIY primary market research of Social Media and Social Enterprise. Our software mines opinions in customers Word of Mouth to measure their engagement with brands and difference between their expectations and their experience, then predicts their propensity for advocacy. For more information about methodology used to produce this information, please visit our methodology page and/or contact the writer.

Spotlight on Customer Engagement

Brand cannot flourish without advocacy of its customers and the advocacy is not likely without engagement.  We have noticed the correlation between number of reviews published online and a number of units shipped, and therefore found it important to use for further studies. There are plenty of smartphones launched every year, but only some engage customers sufficiently to inspire them to share their experience in numbers that are required for meaningful, statistically representative analysis. The consumer exposure (i.e., advertising spent) is one factor, but not the deciding one. An example, HTC 8X, is exposed a lot more via TV advertising than Nokia Lumia 920, but the latter is reviewed online almost twice as much so far.

Samsung is the King of Customer Engagement and it is not surprising that their sales numbers are also leading the rest of the brands. More intriguing is that HTC keeps holding to the second place, considering its well publicized problems.  However the Samsung is not the only net gainer – Nokia has also seen dramatic improvement in its Social Customer engagement.

Below is a chart of the trends in Social Customer Engagement with brands year over year. As the overall engagement grows fast, only Samsung and Nokia show substantial gains capturing attention of this critically important demographics.

The Samsung Galaxy S III was the most often reviewed smartphone in 2012 (5,048), which is remarkable considering its late shipping date.  It is not really a surprise considering its market penetration (it is available under the same name from every major US carrier), and advertizing spent. This strategy does promote powerful Word of Mouth, but this smartphone was also launched before most of the others on this list.The Apple iPhone 5 was second (3,185) and iPhone 4S third (3,096) in engaging with customers.

Customer Engagement with Platforms

It appears that Social Customers display more loyalty to the smartphone platforms than to the brands as they describe their previous experiences with different manufacturer models, but mostly the same operating systems. That is why we also looked at Customer Engagement by platform.

Again, the domination of Android is to be expected even though it came down from the prior year. The dramatic drop in iOS Customer Engagement is very surprising (30% Y-O-Y), but there is enough evidence of the substantial number of iPhone customers who decided to experience Android (9%) or Windows (14%) platforms. It is always easier to show dramatic gain from a low base, but the growth of engagement with Windows customers is nothing less than remarkable at  1,032% Y-O-Y.

Spotlight on Advocacy

In the previous reports we measured Customer Satisfaction with smartphones, and then aggregated these numbers to the brand level. This year we introduced a capability to estimate (or predict) how the Social Customers would respond to the Net Promoter Score® question, if they were asked “On the scale of 0-10, how likely would you be to recommend this product to your friend or family?”. Since we work with unsolicited customer feedback, we have no ability to ask such a question. However, when customers are asked this question their typical response is to replay their experience with the product in their minds, then decide how to answer, based on those memories. These experiences are precisely the same “raw material” that is available in online customer reviews. Our software does the last piece of translating stories and experiences into a score. It is taking common language and translating it into a scale of how strongly the “author” feels about the subject – either positively or negatively.   The chart below shows aggregated NPS for each brand that is produced by calculating weighted scores of the individual smartphones that are associated with a brand.

It would not be surprising that these numbers may substantially differ from the results obtained by a survey if you consider that Social Customer enjoys anonymity that allows them to say how they really feel about their experience. The top Advocacy rating of 2012 is shared by 2 Windows smartphones – HTC Titan II (NPS=55) and Nokia Lumia 920 (NPS=55). Motorola Atrix 2 (NPS=49), Nokia Lumia 822 (NPS=47) and Samsung Galaxy Note (NPS=45) complete the top five smartphones. The basement is occupied by LG Cosmos 2 (NPS=-68), Motorola Droid 2 Global (NPS=-55) and LG Revolution (NPS=-44). These ratings are changing quite frequently. Our software recalculates every time new customers publish their experiences online. Free access to a real-time monitoring of a product category of your choice is available on trial basis.

Advocacy by Platform

Say what you want about a shortage of applications, Windows users just love their experiences with the platform. There is not a lot of them yet (4,152), but their numbers are growing fast (1.032% year-over-year) and they are very vocal. The quarterly growth trends were very consistent and apparently predictive of growing sales  (139% in Q3).

Three out of top five smartphones are powered by Windows.

We cannot provide trending information for NPS this year as this capability was launched only a few months ago.  However, we can look at Customer Satisfaction as a proxy, to see that it improved for all platforms excluding Blackberry.

The blog format does not allow enough space for detailed reports of each smartphone customer experience analysis, or their benchmarking and root cause analysis, but such information is available on request if desired. Below is an example (a screenshot) illustrating a format of Customer Experience dashboard.

In conclusion, this form of Social Media market research offers compounding benefits: faster time to insight translates into advantages in time to market. Lower research costs mean more resources that can be directed into improving the Customer Experience. All this translates into serious competitive advantage. In our experience, companies that leverage customer review data not only benefit from faster time to insight, but actually find the information more actionable.

Here is a copy of our latest press release.

Amplified Analytics launches NPS® capabilities for unstructured Voice of Customer content analysis.

The leading provider of Market Intelligence extracted from aggregated, unstructured Voice of Customer introduces new capabilities for enhancement of its business clients’ NPS® (Net Promoter Score) programs.

NPS, Net Promoter and Net Promoter Score are registered trademarks of Satmetrix Systems, Inc., Bain & Company and Fred Reichheld.

Richmond, CA – (date) – Amplified Analytics, a leader in the field of Customer Experience Opinion Mining, announced today the launch of a first of its kind application that measures Customer Satisfaction without use of traditional survey methods. The application is designed to process high volumes of unstructured consumer generated stories, describing customer experience with specific products or services, and to measure their Customer Satisfaction in the standard NPS format. In addition the system enables Voice of Customer and Customer Experience Management professionals to automatically extract specific attributes of customer experience that impact Customer Satisfaction scores.

Apart from reducing cost and time turnaround of processing their own Vice of Customer content, Amplified Analytics clients report additional benefits of this approach:

1. Ability to include unsolicited Voice of Customer content found in Social Media, that brings much more statistically representative results;
2. An opportunity to generate Competitive Marketing Intelligence by producing NPS scores for competing products/services that are consistent with internal Customer Satisfaction ratings;
3. Automated classification of the content to produce underlying reasons for Customer Satisfaction ratings, along with measurements of their relative impact on the aggregate Net Promoter Score.

NPS Voice of Customer reporting is powered by Amplified Analytics’ proprietary Opinion Miner software platform. Amplified Analytics built it’s reputation as a leader in Customer Experience analytics by providing Social Media Marketing Research services to marketing organizations of Consumer Electronics, Software and  Hospitality companies. The Marketing Intelligence produced helps companies identify why their customers choose one product or service over another and what product enhancements increase customer satisfaction.

About Amplified Analytics

Amplified Analytics is a Richmond, California-based technology company providing Social Media Marketing research and intelligence services powered by feedback from consumers, which is aggregated from multiple sources including publicly available information from product-review sites. Through the use of the company’s reports and Customer Experience analytical data, Amplified Analytics’ clients are able to access the true voice of the customer. Amplified Analytics automatically transforms customer reviews, call center transcripts, emails, chats and other interactions into insight that helps its clients better target consumers’ needs, as well as improve product and service offerings.

A few years ago, while I was looking to buy my first smartphone, I noticed that everyone was trying to sell one to me based on device specifications. No doubt, the specifications, features and functions are important, but it is not always clear how they translate into customer satisfaction with the smartphone after the purchase.

I realized that customer reviews are much better sources of information to help me choose the right smartphone for me. They allowed me to understand better how the phones perform in specific circumstances and to decide which one is the best for my personal priorities.

The only problem with this approach is the time and effort it takes to find customer reviews for the smartphones I am interested in, read through many stories and distill the critical information to help me make the right decision.  I had really good experiences with every product I chose using this approach. Here is an example: Five years ago, I was shopping for a small but powerful notebook for business travel. My technologically superior friend was shopping for a similar device at the time, so I asked for his recommendation. He chose a very popular brand with great specifications and reasonable price. I decided to check the reputation of the recommended notebook and found it to be spotty at best. I spent 58 hours researching customer reviews before making my choice, and it still works great for me, 5 years later. My friend had all sorts of reliability problems with his, and is on his third notebook now.

Now to the good news. You may have heard about the “Big Data” technology that helps governments and large companies to decipher huge volumes of data to produce meaningful and useful information. They use the technology for national security, market trading and marketing research applications, to name a few. Well, now this technology can help consumers to make better smartphone selections based on their personal priorities and massive volumes of customer reviews in seconds.

Here is the site where you can find unbiased smartphone recommendation based on Opinion Mining of customer reviews and your personal priorities – http://www.what-is-the-best-phone-for-me.com/

“Happiness is in expectations management.”

Let’s try to apply this wisdom to Product Marketing and Marketing Strategy. For eample, your company expects a product to generate specific and positive cash flow over a period of its life, and your customers expect the product to reliably perform functions you have promised them in your marketing communications.

I would like to pose that pro-active management of  your customers expectations will dramatically improve the probability of your product’s success.

It is important to take a look at the entire cycle of creation and management of expectations process:

•  Pre-Announcement Speculation Stage- Think about rumors and speculations about the “next” version or release that start to appear out of nowhere soon after a new product is launched. Regardless of the sources or “accuracy” of the information floating around, the consumers started to expect that Apple iPad3 will have smaller size/track form than iPad2 just two quarters after iPad2 was launched.Who knows how they will react on the announcement day if this expectation is not met? Should the speculations be ignored? Can they provide early predictions, hints and insights that help to form consumer expectations? Can they negatively affect the market performance of the current model as they influence consumers to delay their purchase until speculated new model is launched? Most importantly should they influence the strategic planning process?

• Product Announcement and/or Launch- Now, the mysteries of a product’s specifications and major functions are revealed to the public; however, the interpretation of this data is done not by the consumers at large, but by a relatively small group of analysts, pundits and bloggers who are well aware of expectations created at pre-announcement stage. Some of them probably have created or at least communicated these rumors and speculations. Now they have to reconcile the speculations with the announced specifications, and of course to write about it because that is what they do.Many uncertainties are removed now, but performance speculations are sometimes intensified. A good example is the RIM PlayBook battery’s poor performance media storm which somehow petered out by the time the tablet started shipping. By that time the PlayBook was perceived by consumers at large as a problematic product. I am not suggesting that this issue alone caused the tablet to fail RIM’s expectations; however, a mismanagement of “signals” like this one is not a recipe for success.

• Pre-shipment- It is quite a common practice today to let influential industry/market analysts experience product before the general population of consumers. There are pretty strict guidelines involved in this process to maintain proper relationship and ethical standards. I am not writing about a practice of buying endorsements to full consumers; this practice is now illegal. You probably read critical acclaims to a movie that yet to be released to the theaters or criticisms of video games that are not available yet to players. The idea is to create a positive impression enough that would engage early adopters into a first wave of product moving through the channels.The articles and reviews published by the pre-shipment stage influencers are a gold mine of the feedback for potential “last chance” reconciliation between expectations and experience. However the time for analysis of this feedback, the identification of “low hanging fruit” opportunities for changes, their prioritization and the implementation is very, very short.

•  Product Shipped – Now, the early adopters – your very first customers -  got the product in their hands. Their expectations are formed by your marketing messages, their previous experiences with your brand, and the reviews of the pundits published during the pre-shipment stage. These early customers start to share their experiences generating Word of Mouth (WoM) online as well as off line which, according to multiple research studies ( example 1, example 2), is the most trusted source of information that influences consumer decision to purchase your product, or select the competitor’s.Many marketing pros told me that they are aware of the WoM’s importance, and confessed to searching and reading as much as they possibly can. Some use Social Media monitoring tools to detect a sentiment and to know whether their product is liked or not, but cannot figure out WHY. None of these approaches can detect and consistently measure the difference between customer’s expectations and experience, but it can give you some hints. The critical question is, “what are you going to do with such information?”

We have seen the most powerful results achieved and the most attractive ROI, when marketing used the feedback analysis results to:

1. Engage market players by clearly communicating these results and the company’s plans to act on them;
2. Fine tune Marketing Communications messages and media to resonate with customer’s perspective found and measured in WoM.

This approach may involve multiple departments in some organizations, from Product Marketing to Marketing Communications, PR and Customer Service, to mention a few. Each has its own perspective on interpretation and value of customer feedback and WoM – some treat it as Crisis Management and some ignore as anecdotal trivia. However, this is the best expression of how well your product met customer expectations well before the sales numbers spell it for you. By that time the “game” may be over.

This article titled “Best Buy struggling as shoppers flock online” was published in San Francisco Chronicle caught my attention and inspired me to question the title assertion.

“The one critical thing we offer the world is choice,” said the Best Buy chief executive officer Brian Dunn in a March 2012 phone interview. He was trumpeting in particular his company’s role in guiding customers through the expanding smartphone universe.

“We provide the latest and greatest choice of all technology gear, from Apple products to Google products, and that brings more opportunity to help people put technology to use. That is a great place for us to be.” A week later, reality intruded. The consumer electronics retailer posted a $1.7 billion quarterly loss and announced it would close 50 stores nationwide. On Tuesday, Dunn resigned.

Later in the same article, this reason was cited to explain Best Buy’s fall from grace of consumers:

“Shoppers are finding more choices online, primarily at Amazon.com, where they can often find a better deal.”

Price is the favorite excuse of every salesman who failed to earn the trust of the customer. It is interesting to look at the Customer Intelligence Analysis of the feedback given about experience of doing business with Best Buy. We have looked at 185 customer stories that describe their experience during a period from 1/1/2012 till 4/17/2012, the date this article was published.

I would like to point out that the “price” was opined on only 4% of all opinions expressed, and the sentiment is statistically neutral while “customer service” is the most mentioned by customers at 42%. It is decidedly disappointing to them with a “general satisfaction” score of 0.67 (see the score legend at the top right corner of the image above).

Perhaps the analysis of a larger number of customer feedback for a longer period of time would show exactly when Best Buy started to lose its competitive advantage and push their customers away. However, I would like to suggest that the “greater selection” strategy has definitely played an important negative role in the Best Buy decline. There are three reasons for this suggestion:

1. No brick and mortar store, regardless how big it is, can out-inventory an online operator like Amazon.com that does not need to have an inventory on hand to sell products and have a network of store to fulfill orders;
2. A very large selection of products on shelves results in poor support for most products as the store personnel cannot keep up with knowledge requirements for such a vast number of products. Many customers come to store seeking for help to select a “right” product for them, and Best Buy staff fails to do it;
3. The larger selection leads to lower quality of products being sold to consumers. Look at “reliability” bar on the chart above—26% of all opinions mined are indicating a miserable satisfaction with the quality of products sold by Best Buy stores
4. 

Couple this problem with the well publicized Best Buy return policy issues, and it becomes clear that it is easier for customers to deal with online stores than less expensive.