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.

Most company executives don’t think that their accounting department is in the Customer Experience business. True, very few members of financial management teams normally have a reason or opportunity to communicate directly with their company’s customers unless they have to chase accounts receivable problems.

The new CFO of a start-up I was working for took pride in maximizing operational cash flow velocity. One of the minor tactical tools used was a few days’ increase in the window for reimbursing employees’ expense reports.  This change handsomely improved the short term cash flow statement. However, over the next few quarters, a noticeable trend in the growth of outstanding accounts receivable started to raise red flags and call for analysis.

You may ask what this has to do with Customer Experience Management. Interestingly enough, all measurements of customer satisfaction and loyalty, both objective and subjective, started to move in the opposite direction from the operational cash flow velocity metric within the first two months of the change in reimbursement policy. The Customer Experience Manager was reporting this troubling trend for months, but nobody thought of a connection. In fact, nobody ever looked at financial and loyalty metrics together at all, and that is why it took so long to link the cause and effect.

Cashflow velocity and NPS

It turns out that the technically complex product the company sells routinely requires professional services personnel to visit customer’s premises to help them ensure successful implementation and operation. The company’s engineers spent a lot of time making customers happy, and the company was paid well and on-time for their efforts. However, improving the velocity of the company cash flow negatively impacted personal cash flow of the front line employees, as they had to wait for sizable expenses to be reimbursed and had less cash for their personal expenses. They started to avoid and delay the projects that required travel, and customers fell victim to financial efficiency efforts.

Lessons Learned:

• Customer Experience is a holistic matter – every single function of the company affects how customers perceive the entire enterprise. Of course some functions affect more than others, but they all do.
• The Customer Experience measurements are predictive of the growth or demise of a company (product or brand). The trends are critical indicators of trouble, particularly if they are gauged against market averages.
• Monitoring the correlations of trends between Customer Experience, Operational and Financial metrics allows for the fast diagnosis of potential treats to the health of your business.

Customer perceptions of products and services, or companies and brands, are measured using different scales and methodologies. Regardless of any ambiguity of definitions and sophistication of methodology, any scale you choose reflects a fundamental consideration: how does the product (service/brand/company) experience compare to customer expectations? The expectations are formed by a company’s marketing communications and advertising, other consumers’ word of mouth and (in this age of the Social Customer) pundits and existing customer reviews published online. There are many well documented ”purchasing journey” maps produced by respected researchers. Here is one example.

Most of the studies agree that the choice a customer makes is based on the expectation that the selected product will be more satisfying than most other products within the segment. Yet, many businesses measure the Customer Satisfaction of their offerings without comparing the results to their market averages. Considering that these sentiments are very dynamic, competitive comparisons make the process even more volatile and difficult to measure. However, the results are often well worth the effort, as they generate ideas for differentiation, marcom efforts optimization and operational improvements that could produce significant financial gains.

The example below shows Nokia Lumia products exceeding their customers’ expectations by a much wider margin than their top competitors and the smartphone segment average. If you are involved with Customer Experience Management, a deeper look into the reasons behind the trend may help to improve your customer journey.

The following example measures aggregated Customer Satisfaction with Small (Kitchen) Appliance Brands against average satisfaction level within that Category. It is based on content analysis of 65,379 customer reviews published online over one year period.

Such measurements can be produced using most popular scales (such as NPS or CSAT), done for any market segment that has Social Customer engagement, and results can be aggregated by brand and/or distributed by a channel.

Many business problems that negatively affect Customer Experience have their roots in the siloed nature of an organization. A business often sees itself as a collection of departments, while a customer experiences it as single supplier, provider or brand. Early CRM initiatives promised to fix this problem, but very soon they limited themselves to aggregating and managing front office processes, giving up on the rest. The fragmentation of business processes, KPIs and data flows is a very serious problem that is difficult to resolve because it is ingrained in core human behaviors, which precede corporate environments or any customer experience discipline. Today we measure our personal security by the importance of the knowledge we possess and our ability to control information in our domain.

Few years ago I was contracted to reduce the sales cycle of a very new and technically complicated enterprise software. The optimization of pre-sales support processes was a challenging project. The proposed solution, if adopted, would have resulted in an outcome of almost 50% cycle reduction. The implementation was swift and successful, and executive management, sales and customer support organizations were excited and eager to adopt. However, order management, fulfillment and QA passively resisted and ultimately suffocated the initiative that would bring millions in additional revenue with an improved profit margin.

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 post continues to explore the theme of Unlocking The Value of CRM. Previous installments can be found here and here. This installment focuses on Change:

It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.

Charles Darwin (1809 – 1882)

Most CRM initiatives are launched to change the way of doing business in an organization, i.e. organizational transformation – if they don’t, the economics of such an initiative should be questioned. However, concerns about adoption challenges often shift the focus to functions and features from processes and economics.

Instead of clear communication of goals and benefits to the employees and to the enterprise, and development of a sound, comprehensive change management strategy – the program leadership slips into a risk mitigation mode. The requirements gathering interviews can easily turn into pacifying the participants with discussions about laundry lists of functions and promising no changes to the underlying processes.

Principal concerns of business community involved with proposed CRM initiative are:

1. Increased work load expectations;
2. Negative impact on personal income and earning ability (SFA) caused by sharing Contact and Opportunity information;
3. Increased accountability for quality of forecast translated into job security.

I often focus on SFA adoption challenges while discussing CRM initiatives because these have by far the worst history, and are considered the most difficult to navigate. Most Customer Support, Call Center, Marketing and other CRM related initiatives have much better adoption record because their processes traditionally are more clearly defined and managed for for consistency.

Salespeople, on the other hand, focus on an event rather than a process, and see any attempt to dissect selling process for analysis with great contempt as they regard selling as an art form. While sales professionals do not respond positively to management, they do respond very enthusiastically to leadership and basic economics:

• Architect the implementation for their benefit, and not exclusively for the benefit of their management.
• Well thought through changes to sales compensation structure to influence their behavior will produce very powerful results. Needless to say these changes should influence behavior specific to achievement of  financial goals of CRM initiative, not paying for use of the system.
• Consistent publicity for sales community leaders who embraced the change and financially benefited as a result.
• Steadfast and brutal treatment of any attempt to misuse shared information for “poaching” purposes.
• Maximize automation of initial data loads and subsequent data capture.

Most of business managers would like to make informative business decisions rationally based on data and evidence, and yet corporate meetings are still too often dominated by “vision” and “gut feeling” arguments. It is easy to argue that uncertainties of the market landscape are impossible to predict, and one never has enough information at any given time. This is a difficult argument to counter, but there are examples that show data driven decisions are possible and they dramatically improve the results, when used properly.

Consider commonly used GPS device/service for your car, that allows you to predict your arrival to the destinations of your choice with a relative accuracy, even when you do not know the directions in advance. Later versions are even capable to route based on current traffic conditions. Think about this as an analogy for providing vital business information to support management decisions. Understanding what makes GPS so indispensable for driving vehicles can provide ideas for design of  service indispensable for driving business decisions.

1. No reasonably accurate position reading is possible without a minimum of three satellite signals. In business environment these “satellite” signals may be Market, Customer and Company data sources. The intersections of Financial, Operational and Customer Satisfaction metrics could provide your product, brand or company its current position reading with relative accuracy. All of these data streams are  available either from internal and/or external sources, but the synthesis process of federating the data and its correlation into “objective” metrics is not commonly observed in practice.
2. The positioning is critical as a starting point, but without availability of cartography the GPS would not be as useful. From the perspective of business, a combination of Customer Intelligence (transaction history, relationship history, satisfaction/loyalty data and utilization analytics), Market (non Customers) and Employees perceptions, form the maps for charting the course of business decisions. Most of this data is available only in unstructured format and therefore largely ignored by many BI/Big Data initiatives.
3. GPS routing algorithms use Operational (speed), Intelligence (traffic conditions) and Cartography information to suggest available decisions to reach desired destination and to predict likely time of arrival. Use of predictive analytic models is relatively common for investment management, banking and national security. I yet to see them used in product management, marketing or sales operations applications.

There are a lot of layers need to be peeled from that “onion” before any specific, functional solution can be crafted for your organization. The important things to remember are:

• You can buy technology tools and data access sources, but you cannot buy the solution for your business. The true solution requires fundamental understanding of your industry, clear comprehension of your marketplace and intimate knowledge of your company. Not too many business practitioners would publicly acknowledge their belief in magic, and yet they keep shopping for the magic bullet.
• Predictive models are just that – models. Just like GPS sometimes can suggest a wrong turn, these models cannot guarantee the best decision. However, they can consistently improve quality of management decisions that would translate into consistently better profit margins, earnings per share, or whatever other metric you want to apply. The idea is not to predict the future, but to estimate probabilities of specific outcomes to be realized, based on specific actions and conditions.
• Resist the temptation to use the models in autopilot mode – that is the shortest route to disaster.  The most recent example of this unfortunate practice in business is the 2008 financial crisis. The best example of such behavior in use of GPS is described Newport-to-Ensenada 2012 race tragedy report.  Regardless of the model quality, the decision maker, driver or skipper bear ultimate responsibility for the decision output.
• The most valuable insights are hiding near intersection of multiple data sources. Use innovative, holistic thinking to optimize your business processes and practices, instead one-dimensional approach.