I am kicking off a research stream which will result in the "Text Analytics Roles & Responsibilities" doc. Before I finalize an RFI to our clients to see who/how/when/where they employ for these projects and applications, I'd like to explore what the actual roles and responsibilities are. So far we've come up with the following roles and their respective responsibilities
Business owner. The ultimate recipient of text analytics process results. So far I have
Customer intelligence analyst
Customer service/call center analyst
Competitive intelligence analyst
Product R&D analyst
Linguist/Data Scientist. Builds language and statistical rules for text mining (or modifies these from an off-the-shelf-product). Works with business owners to
Create "golden copies" of documents/content which will be used as base for text analytics
Works with data stewards and business ownes to define corporate taxonomies and lexicon
Data Steward. Owns corporate lexicon and taxonomies
Architect. Owns big data strategy and architecture (include data hubs, data warehouses, BI, etc) where unstructured data is one of the components
Developer/integrator. Develops custom built text analytics apps or embeds text analytics functionality into other applications (ERP, CRM, BI, etc)
Beware of insights! Real danger lurks behind the promise of big data to bring more data to more people faster, better, and cheaper: Insights are only as good as how people interpret the information presented to them. When looking at a stock chart, you can't even answer the simplest question — "Is the latest stock price move good or bad for my portfolio?" — without understanding the context: where you are in your investment journey and whether you're looking to buy or sell. While structured data can provide some context — like checkboxes indicating your income range, investment experience, investment objectives, and risk tolerance levels — unstructured data sources contain several orders of magnitude more context. An email exchange with a financial advisor indicating your experience with a particular investment vehicle, news articles about the market segment heavily represented in your portfolio, and social media posts about companies in which you've invested or plan to invest can all generate much broader and deeper context to better inform your decision to buy or sell.
But defining the context by finding structures, patterns, and meaning in unstructured data is not a simple process. As a result, firms face a gap between data and insights; while they are awash in an abundance of customer and marketing data, they struggle to convert this data into the insights needed to win, serve, and retain customers. In general, Forrester has found that:
The problem is not a lack of data. Most companies have access to plenty of customer feedback surveys, contact center records, mobile tracking data, loyalty program activities, and social media feeds — but, alas, it's not easily available to business leaders to help them make decisions.
Are you looking for a vendor or vendors to support your voice of the customer (VoC) program? Or are you reviewing your current VoC vendor(s)?
Selecting the right vendor or vendors can be hard! Why? The VoC vendor landscape is hard to decipher. There are many but relatively small vendors, and they rely on an interconnected network of partners, acquire each other at an impressive rate, and regularly expand into new spaces. And companies often already have a number of vendors they work with. In my recent webinar about VoC, most of the attendees had from three to five vendors that supported their VoC program in some shape or form.
But there are a few beacons to help orient you in your quest:
The VoC vendor market is an ecosystem. What vendors are the right “lid” for your “VoC program pot” depends entirely on your internal capabilities and the characteristics of your VoC program. We identified customer feedback management (CFM) platforms and VoC specialist vendors. CFM platforms support VoC programs with a robust set of capabilities that include feedback collection, integration of feedback with other data in a centralized data hub, analysis, reporting, and closed-loop action management. VoC specialists offer a subset of VoC platform vendor capabilities. Their areas of expertise range from surveying customers in order to generate measurement data to mining your unstructured feedback with text analytics, monitoring social media data, and consulting to help establish or evolve a VoC program.