Lowering "Break Even" for justifying Text Analytics

In a world where most businesses doing customer and employee types of feedback still "code" their verbatim survey responses and other text feedback manually, the standard for "break even" on automated text analysis solutions generally seems to be on the order of ten thousand 10,000 text items per month.

Why is 10,000 the number?  In my experience, I've seen many instances where smaller volumes would justify investment in an automated solution.  Yet, to a large degree only very large businesses and government agencies with big flows of  text based feedback have adopted automated text analysis solutions. 

I think there are two reasons for this.  First is the price of the automated text analysis solutions, which typically have minimum annual costs of $100,000 per year.  So, for a business with lots of text to be coded, only when "people costs" exceed $100k/year does it make sense to invest in an automated solution.  The second reason is that people rarely do just verbatim coding in businesses today. Typically groups of people do the work in different departments as part of their regular jobs (VOC Analyst, Market Research manager, etc.). There's often no single FTE that can be "replaced" by an automated solution.  Only when the volumes of feedback become so large as to be overwhelming do businesses consider automating the analysis process.  By then, the costs of manual coding are large and they justify a large investment.

But, what would happen if the annual software cost of an automated text analysis solution could be lowered to $50,000 per year?  I think that the potential market for automated text analysis would become exponentially larger.  After all, in most businesses its a lot easier to find half of an FTE doing text analysis manually than it is to find full FTEs manually doing text analysis. 

In my opinion, there are additional reasons to consider automating text analysis at lower levels of feedback than 10K per month.  Just one is the ability of an automated solution to identify new topics.  As someone who does a number of feedback projects that employ survey based open answer questions, I regularly evaluate verbatim responses both manually and via automation.  Whenever I've used etuma360 I've found that the etuma analysis identifies topics which I had not considered based on my manual inspection process.  And, since people doing manual coding have a propensity to map all the incoming feedback using the existing coding structure and categories, manual processes will tend to miss new topics.  Automated solutions will typically pick up the new topics.  Valuing this capability is difficult though.  But, its something to consider when looking at text analysis and its cost benefit.

Etuma has a number of pricing plans that allow businesses to get into automated text analysis for less than the $100K/Year price point.  I would think that anyone with 2,000 pieces of text feedback per month would be candidates for an etuma360 implementation based on FTE considerations alone.

Surveying for Feedback/Response Action Management

Periodically I see discussions in articles and LinkedIn forums about the "Death of Surveys".  But, in my view, the on-line survey business is simply transforming from a focus on surveying for data collection to one of surveying for feedback and response action management (F/RAM).  This is particularly true, I think, in the case of relationship surveys (customer, partner, employee, alumni, union member, donor or "membership" types of surveys).  In short, where "relationships" exist between an entity and a population of people, something more than data collection is now necessary. 

In my view, surveying for relationship management purposes is occurring more today because of the growth of social media, on-line chat and mobile device technologies, all of which help businesses collect huge amounts of customer data. So much so, that businesses are almost overwhelmed by it. It's not a coincidence that data analysis, "big" data and data storage vendors are doing well.  All that data needs to be analyzed, correlated, cross referenced and stored.  Yet none of it really triggers businesses to build better relationships with the people they interact with.  Somewhere and some how, somebody has to ask customers how they feel in order to assess relationship quality.  If a business has lots of customers, a feedback/response action management survey is the best way to do that, because the feedback automatically propagates dialogue in a F/RAM process.

Feedback/response action management is a process that many businesses are unfamiliar with.  Its a fair bit more complex than traditional market research.  It relies on customer data to guide how response action management should be implemented and it necessitates the use of a methodological approach (NPS, CSAT, CxM or something similar).  In addition, F/RAM requires that feedback scenarios be modeled or at least thought through, so that appropriate responses can be formulated (i.e. who responds and how when a customer - from country x, with product y and issue z triggers a response action based on their survey feedback). 

A number of on-line survey platforms today can implement an F/RAM process.  Some of the platforms though are expensive to acquire.  My admittedly incomplete list of F/RAM capable tool sets includes: QuestBack (all platforms), Vovici, Medallia, Allegiance and ConFirmIT.  ClickTools and KeySurveys to my understanding only implement F/Ram processes through CRM integration (and ClickTools only for SalesForce). In my experience, almost all the other tools  "out there" are primarily focused on just data collection and analysis.

In my experience there are two critical capabilities that a tool needs to have in order to implement an F/RAM process.  First a tool needs to be able to trigger a real-time follow up action based on a survey response, customer data or a combination of both.  Second, a tool has to be able to link, in real-time, customer data to the survey at a respondent level.  Without these two capabilities F/RAM processes require lots of I/T intervention in order to get survey responses to trigger actions at a respondent level.