Good Customer Surveys are Money-in-the-Bank

Being in the customer experience management (CXM) space over the last seven plus years. And, in customer facing roles for a lot longer than that, I've seen first hand how customer feedback can impact businesses in hugely positive ways. At the same time, I see how customer feedback is often mis-used, or worse, goes unused at all. So, I thought I'd post something about the many ways that customer feedback can mean money for businesses.  Here's five examples...

1. The customer relationship survey. I constantly read about how companies are de-emphasizing their customer surveys because of low response rates, non-actionable data or other problems.  What I know, from long experience, to be true is that customer relationship surveys are hugely valuable. Consider the math. If you have ten thousand customers, a 10% churn rate, a 25% recovery rate and an average revenue of $1,000 per customer you lose a million dollars of business yearly, and get a quarter of it back after working for it again.  If you can cut that by a third, its an over three hundred thousand dollar "gain" to the company, and its less effort / investment put into account recovery afterward. Needless to say, you need less new customers to get back to even and if you get the same number you are up. Customer surveys provide the indicators and insight you need to reduce customer churn before it happens.
2. The customer relationship survey redux. Companies invest lots of money in developing testimonials. Smart companies just ask for feedback then take the words their customers write, feed them back to the customers along with a request to re-use the feedback in their marketing. Each instance becomes a virtually free testimonial.  With today's social media tools, its simple to automate feeds of positive, customer approved, feedback straight to your Facebook page, Website, Twitter feeds, etc...
3. Sales lead qualification surveys. Companies today invest boatloads of money in in-bound lead generation. They then bombard the "leads" with marketing e-mails (LinkedIn lives off of this). The leads after a while will self select away from the company to avoid bombardment. But, the real problem is that they don't really know who truly is a lead and is worthy of nurturing. A simple survey "leads" what they think of their solutions and likelihood of buying at some future point would produce a much clearer picture of who really is a lead and who isn't. Cost of this? Very low. Business impact, very high as "leads" who self qualify are much better quality (as any semi-seasoned sales guy would tell you) than those who do not. The survey process has the additional benefit identifying leads as qualified before those leads would otherwise do so via a normal bombardment process.
4. Prospect validation surveys.  As a sales manager I have found that sales reps can be opaque at times about their sales funnels. Often they truly do not know why a prospect isn't advancing through the funnel or that a lead hasn't yet defined themselves as an opportunity or that a prospect deep in the funnel in danger somehow. Surveys can provide give them (and you the manager) the insights they need to properly determine positioning in the funnel.  
5. Product / Service value surveys. Product managers are constantly trying to determine what features, capabilities, add-ons, integrations or other "things" they can add to their company's products or services.  And, determine which things they do will help the product maximize value to the company. Surveys asking customers for product thoughts (i.e. problems, enhancement ideas, documentation improvements, etc....) are an easy way for this kind of data to be accumulated.  Getting product enhancement ideas early and constantly helps product managers keep products current or ahead of with market requirements. Products that stay consistently good relative to competition often have more loyal user bases and higher overall profitability - Money in the bank.

So how to do all this surveying without over surveying customers and reducing responses rates?  First off, don't create one big survey and send it to everyone. Segment your customer population, then survey the segments periodically as business needs dictate. For example, survey product users for product management - maybe yearly or twice yearly. Survey decision makers and recommenders for relationship quality 1x or 2x per year. Survey leads for qualification quarterly.  Survey prospects for prospect validation - once if in short sales cycle and twice or more if in a longer cycle.  

What else to do. Have a process for acting on all the feedback you get. Its important to ask for feedback. Its more important that when feedback comes in someone, somewhere in your company sees it and take an action on it. 

Surveying customers in the right ways, at the right times with the right actioning processes in place is Money-in-the-bank.  

Learn more about QuestBack and how we can help with your customer surveys.

What's the next consolidation in EFM?

There's been a large recent influx of new capital going into EFM vendors, either through private equity, or merger and sometimes by both merger and additional equity. So, I thought I'd revisit my thinking on the consolidation occurring in EFM.

All technology markets undergo consolidation over time. Normally, it occurs as the technology itself (whatever it is) grows and vendors adapt to that growth. This has been steadily happening in the EFM space.

A few months ago I wrote about this in a post titled: "More Consolidation in the EFM space." It outlined the merger and acquisition activity going on with EFM. The discussion was about the business consolidations by Verint (Vovici), ConfirmIT (CustomerSat), SurveyMonkey (CustomerSat and ClickTools) and others, including QuestBack. The post is available here:

At the time, I had three thoughts about the merger activity.....

"Thought #1.  The EFM space is getting crowded at the top end of the market.  Gartner, Forrester, Aberdeen and others have been beating the drum for Enterprise Feedback Management for a long time, at least five years by my count.  Since most of the EFM vendors focus their efforts on selling to "Enterprise" class customers, as time has passed more of them have adopted solutions, leaving less growth available to the rest of the players.  Hence, acquisitions of high-end products."

Clearly, the EFM space remains quite competitive at the top end of the market. So much so in fact that EFM vendors are competing with market research consultants, who sit at the top echelon of the market and act as strategic vendors to large businesses. ConfirmIT / CustomerSat and even QuestBack / Global Park seem to be pushing into the project space of traditional market research consultants. Market research consulting firms are reacting by acquiring EFM technology vendors. The Empathica / Mindshare and Maritz / Allegiance mergers look like this kind of combination to me.

I'm not sure how this will play out. Consulting firms typically purport to be "tool agnostic". It may be that these particular companies have vested interests in the survival of Mindshare and Allegiance, having brought those products to customers as part of solutions. If that were the case, it argues against the standalone market effectiveness of those products going forward. Alternatively, it could be that the consultants find a strategic advantage to owning their own EFM products. Potentially they've even acquired significant projects or new customers as a result. From the outside there's really no way to tell.

To me though, when I see technology solutions that require large amounts of consulting support to enable success, the benefits of the solution need to be correspondingly large, usually this means enterprise scale. Ultimately, I think that means the enterprise software guys will be sniffing around at EFM companies too.

"Thought #2.  Serving the small and mid-tier customer segments normally requires that companies have either scale or distribution in order to effectively market.  SurveyMonkey has scale, QuestBack has distribution (I'm a QB reseller), Vovici has partnerships (Oracle in particular) and ConfirmIt now has scale at the high end of the market."  

Since publishing my earlier comments there've been changes at these companies. SurveyMonkey, QuestBack and ConfirmIt have all become more potent competitors via organic growth and acquistions. What's really new is that Qualtrics and Satmetrix have joined the ranks of larger players in the market. The common theme among all these firms is that they now all have scale, breadth of market access and technology competency. It's a good bet that all of them will continue to grow. Some may become targets themselves for the software giants out there looking to acquire saas businesses in the EFM / CXM space.

Thought #3.  Many of the smaller players in the EFM market have neither scale nor distribution. They have to rely on organic growth while competing with larger, better funded and more effectively structured companies.  It is among this group of companies that I expect to see further consolidations.  Some companies on the list:  Qualtrics, Medallia, Satmetrix, Allegiance, SNAP surveys and KeySurveys.  These firms serve Enterprise customers or mid-tier customers using a direct sales or assisted direct sales model. They could all use more scale, more distribution or both.

Not much new here except that the list is smaller. Some companies have moved up and others have been acquired. The rest, in my opinion, will be bought out or will just continue muddling along.

So what's next for EFM?

I see EFM being subsumed into the Customer Experience Management (CXM) space. Businesses today realize that feedback comes to them via multiple channels and in different forms. CXM has been about finding ways to collect and integrate that largely unstructured feedback with standard and more structured feedback processes. The goal being to produce a coherent view of customer perceptions, issues, advocacy and angst as it relates to products and processes. The point is that EFM / CXM's value proposition has moved largely to back-end analyses and visualizations which document insights and facilitate actions that improve customer experience.

Text Analysis with almost No Manual Effort

Last week I posted what was, essentially, a critique of manual word cloud based topic mapping processes. These types of manual processes are very common among survey tool vendors who are trying to incorporate text analysis into their solutions. The critique I made was based on the notion that doing lots of manual work on word clouds and topic maps is unnecessary.  In this week's post, I'm going to try and show a better way, using Etuma360.

All text analysis has to start with a stream of text. The text can come from web forms, chat logs, forums or Surveys. Using Etuma360, that text develops a word cloud that represents the usage of words in the text stream. Rather than manually mapping words topics, what if the text analysis system already possessed a topic database that words in the word cloud were mapped to?  This would eliminate almost all the manual effort involved in word mapping to topics. Exactly how the Etuma360 product works.

A text stream is fed into Etuma360 using either a file upload or an API process.  In this case from a customer survey uploaded to Etuma360.  A word cloud is automatically generated.....

And a topic / sentiment list is also Automatically generated.  No Manual Effort required.....

Because Etuma360 does the topic mapping automatically, the analyst can focus on the visualizations his end users need......

As I said, Easy, Fast and Effective.  Consider how much money a survey analyst makes and how much time they have to spend mapping words to topics.  If its 100 hours in a year and $100 / hour.  Cost is $10K. And, that's before buying software or generating any useful analyses. Etuma360, saves you all that labor cost and more.

To take a free trial of Etuma360 Click the link below:

 https://response.questback.com/demo_nash_stewart_qbbostonusa/etuma90daytrial/

Analyzing Survey Open Ended Questions

I've been on the distribution list for Survey Magazine (electronic version) for several years now. Recently, they published an article (I think sponsored by Cvent) about using text analysis on survey open ended questions. Though the article offers some useful advice, it seems to me that there are better ways to do text analysis on survey open ended questions than the methodology proposed in the article.  So, I thought I'd discuss some of the main points made and offer some thoughts. For those interested, the url below will bring you to the entire article. For clarity, I've italicized material from the article and colorized, in blue text, my remarks.

http://viewer.epaperflip.com/Viewer.aspx?docid=b3b90dd4-b2bd-4945-8af1-a36100b7c43e#?page=36

The Survey Magazine article begins with the basics about why its important to do text analysis. It goes on to make two points: First, that analyzing text is difficult and why ("The hardest part about including open-ended questions in your survey is analyzing responses. Unlike close-ended questions, it’s doubtful that any two open-ended responses will be exactly the same."); Second, it states that a text analysis plan is necessary. The article goes on to share how to create such a plan.

I would agree that analyzing text is difficult, especially using a manual inspection method coupled with word or phrase searches. I also agree that doing text analysis offers lots of value and insight in the right scenarios. But, in my opinion the methodology proposed in the article is "the hard way" to do text analysis and even so will really only be useful on shorter ad-hoc surveys.

The article outlines five steps in a proposed text analysis process.  

1. Use word cloud technology. The best way to begin your text analysis is by using word cloud technology. The technology sifts through responses and creates a visual representation of the most frequently used words or phrases. The larger the font of the word in your cloud, the more relevant it is to your data. Once you've seen which words pop up the most, you can start to make categories to group responses and analyze trends.

Almost all verbatim analysis technology uses word clouds in one way or another. More sophisticated products combine words or phrases with usage context. For instance, in Retail e-commerce situations words like "Web site" and "Click" show up all the time. But, analyzing them is valueless without more context.  Manually ascribing that context is a major endeavor if any real response volume is involved. So, the process outlined is very manual and ultimately subjective to the analyst mapping the word or phrase to a category. Another analyst at another time might choose to map the same data to a different category, based on their own interpretation at the time (so there's multiple dimensions of subjectivity). Word clouds are useful tools but are not the "end all" to text analysis.

2. Establish categories. The next step in analyzing your open-ended responses is creating categories. Use your word cloud for insights into the range of thoughts and feelings articulated by your respondents. For example, if you asked customers how they think your organization can improve its product, and the words “cost”, “size”, and “color” loom the largest, create categories for those words. Once you begin to read your responses file them under the appropriate categories. If any of your responses fit more than one category, put them in both.

This is largely good advice. But, again its lot of manual work that would have to be repeated on a survey by survey basis. Several commercial text analysis systems I am aware of (including Etuma360) will do this kind of work automatically and then let you tweak the topic analysis produced, saving boatloads of time. And again, building subjective categories can be potentially problematic, for reasons discussed previously.

3. Review and refine As you begin to inspect responses more closely, you will probably find that you have to make adjustments to your categories. If responses used similar words to describe conflicting sentiments, you’ll have to create new categories; if the reverse is true, you can combine categories.

If you've implemented a manually constructed and word cloud based approach, this is good advice. Language is a living, dynamic construct. Interpreting it is always a "tweaking" process. Just, there's a better way to do it than the process proposed. At Etuma, we use a set of layered ontologies to map language meanings to our topic database. Effectively, this lets us use input from hundreds of our users to improve everyone's language interpretation, largely eliminating the need for each customer to always manage that process. Other text analysis tool vendors employ statistical mapping models that they tweak for individual scenarios and customers. Point is, "topics" found in text streams should be largely auto identifiable, especially in known contexts like customer service or e-commerce. 

4. Make correlations. Now it’s time to examine the text within the framework of your overall survey. Start to couple open-ended responses with corresponding close-ended responses to draw conclusions about why respondents gave the answers that they did. If you used an open-ended question as an avenue for respondents to give an “other” answer to a multiple choice question, try and determine if there is a clear winner. You should also cross tabulate your data by demographic to see if any patterns emerge. Find out if certain groups within your sample tended to answer open-ended questions in the same way.

Clearly, this is something that should be done.  And again, in my opinion there are better ways to do it than that proposed. At Etuma, we simply connect the entire survey (and background data set) by api or upload process and automatically connect topics with filtered data subsets based on survey response categories. It's a lot less work and the analyses produced simply auto update over time.  

5. Summarize your results. After you analyze your results, summarize your findings and include any quotes from the text that were especially illustrative of your conclusions.

Of course, summation should be done, but for on-going surveys it has to be done regularly, as the topics people talk about should change over time. 

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Lots of web survey platforms are implementing word cloud based text analysis. As someone who's used text analysis tools (Etuma360 primarily) for a couple of years now, I find that it is of limited value unless certain criteria are met. Some of those are:

• Larger surveys with lots of open ended responses  
• Permanence. Surveys that run over long periods of time are better suited for coupled text analysis than surveys that are ad-hoc
• Lots of background data about survey respondents

The article in Survey Magazine outlines some useful advice. In my opinion it is more useful for smaller, research oriented types of surveys (ad-hoc with a few hundred responses). For larger long running operational surveys, the text analysis approach outlined in Survey Magazine will be a lot of work. Using something like Etuma360 (www.etuma.com) for text analysis on larger and on-going surveys makes a lot more sense.

To try Etuma360 click here:

A cool new QuestBack Video - check it out.

If you follow this blog at all, you know that I represent QuestBack AS. QuestBack has some really good products but is far from a household name here in the U.S.  And, every now and again they do something really "cool" from a marketing perspective too.  The video below is one such example.  Click Here and check it out.

Stewart Nash

LinkedIN: www.linkedin.com/in/stewartnash