7 Steps to True Actionable Insight from Real-Time Multi-Channel

Feedback Sources

It is often thought that only Market Research data is strategic. It is true that most social media and event based survey data is more operational in nature but when you combine all data sources into a single meta data set, strategic information can be derived from pattern changes. But in order to have reliable good data, certain steps need to be taken. This presentation outlines the steps to ....

REAL-TIME MULTI-CHANNEL FEEDBACK

From periodic market research

projects to continuous actionable

insight

Continuous Actionable Insight

NPS NPS NPS NPS NPS NPS NPS NPS NPS NPS NPS NPS NPS NPS

Social media and customer service

Market Research Project

Market Research Project

Market Research Project

Market Research Project

TREND: FROM MARKET RESEARCH TO REAL-TIME MULTI-CHANNEL FEEDBACKFor about a century companies have conducted market research studies in order to find out how their customers and potential customers feel about your and competitors' products and services. Almost always these studies are done by 3rd party market research companies, who based on a sample either send a survey out (paper or web) or call the customers. Market research is a good and proven way to gain competitive advantage but it has some flaws:

1. In b to c business it is always based on a sample.2. Project from the start to having all the data gathered and analyzed can take a lot of time. Usually weeks but often months. 3. Opinions are solicited. They are not spontaneous. 4. Feedback giving is disconnected from the moment of actual user experience when emotions run raw and real.

What we need is a solution that, while not replacing market research, brings a crucial additional data flow, which avoids most of the market research's short comings.

MANY CHANNELS AND METHODS

Cover all customer segments and

touchpoints

SMS

PAPER

FORUMS

PHONE WEBFORM

EMAIL

METHODS

SURVEYS

EVENT

SOCIALMEDIA

CALLCENTER CHANNELS

MULTI-CHANNEL MULTI-METHOD FEEDBACK IS CRUCIAL FOR ENSURING THAT ALL CUSTOMER SEGMENTS AND TOUCHPOINTS ARE COVEREDWhile market research is still crucial piece of product testing and market entry decisions and in overall strategy formulation, there is strong trend towards real-time, more spontaneous feedback. That type of often unstructured multi-channel form of data brings a set of challenges that need to be overcome.

In this blog I have tried to outline in high-level the most important steps to to true actionable insight from real-time multi-channel feedback sources.

Some people like to communicate or receive correspondence via email, some via sms, and others online. Knowing the preferences of your market segments can help you solicit feedback via channels through which they are likely to respond. This will increase the volume of feedback, making it statistically more accurate. Similarly, some people prefer to answer carefully-constructed surveys while others like more open-ended feedback forms. NPS surveys may suit some groups better. By building a comprehensive real-time multi-source feedback solution, you can trust that every customer segment and touchpoint is covered.

But before we dig deeper into continuous real-time feedback benefits we need to study/discuss the wider change that is happening in consumer business. Consumers have gotten much closer to a companies. Previously it was sufficient from companies to learn about consumers (Customer Relationship Management) but today consumers are learning and want to learn about companies.

MULTI-SOURCE FEEDBACK It is all about good data. From good

data you can derive real actionable

insights.enterprise feedback

customer forums

customerservice

social media

CUSTOMER INSIGHT

FROM BROADCASTING TO INTERACTION - FROM MARKET SEGMENTATION TO PERSONAL EXPERIENCE IMPROVEMENT There are two major trends in the way companies interact and gather information from customers:

1. Every company has a web page and almost all have one or more Facebook pages. All but the most traditional industries and companies are more or less active in Twitter. 2. Web and mobile technologies have made it possible to get event based opinions by sending a text message (e.g. NPS process) to a customer right after the actual customer experience (visit to a bank, car maintenance) and in retail industry loyalty programs have made event based

surveys possible.Most companies already have these and multiple other real-time feedback services in place. Market Research is done by marketing, PR runs social media, customer service and help desks are organized under production and product managers run their own feedback solutions using web services like Get Satisfaction and UserVoice. What they fail to do is to combine them all into a single aggregation, analysis and insight distribution service.

AGGREGATION AND ANALYSIS

Transform free-form text into

structured statistically

manageable data

SENTI M ENT

DISC

USSION TOPIC

Text Analysis

A SINGLE SOLUTION COVERING THE WHOLE ENTERPRISE IS REQUIRED FOR GATHERING, ANALYZING AND DISTRIBUTING CUSTOMER INSIGHTYou need to create a solution which aggregates all feedback into a single analysis. Besides date and customer data, often the only common denominator in multi-source feedback data is the free-form text field. Most of the feedback is in free-form text or has a strong free-form text component (e.g. NPS process, event based SMS surveys). Multi-source feedback aggregation and analysis solution must be capable of “normalizing” all that text into a single uniform structured format. And it is not enough to know whole the comment sentiment (LINK TO BLOG). You must be able to know what people are talking about (TOPICS) and the sentiment of each Topic mention. With these two crucial abilities you can turn all feedback including free-form text into statistically manageable format. There are excellent companies to do all this like Attensity, ClaraBridge, Feedback Ferret or Etuma (LINKS TO EACH WEB SITE).

PROCESS 7 Steps to Comprehensive

Multi-Source Feedback

Management

Normalize the Data

Link Customer Identity

Connect Data Sources in Real-

timeCreate Company Specific Ontology

Combine All Data Sets into a Single “Master

Data Set”

Make sure that all the data sources (Data Set) have

uniform data structure. Try to have as many common background variables as

possible

If the customer identity is known due to event or loyalty program or some other means, combine the

key user demographics and purchase behavior data into each

Data Set.

There is no time for manual uploading of Data Sets. All data should flow continuously or as close to real-time as possible.

Because most of the data is free-form text based, an automatic,

often multi-language text analysis functionality must be

included. Because industries and companies are different a

customized ontology needs to be created.

All Data that has comparable structure should be aggregated to a master data set for PR, marketing and risk management purposes. Source should become a new

background variable

Distribute Actionable Insight

Based on Roles

Create a dashboarding or a real-time reporting system in which

people can have access exactly to the data that is relevant to them. Dashboarding system must allow

setting rules based on background variable or text analysis topics or sentiment.

Make Resuls Available to Big Data Analysis

Make the analysis results available to 3rd party CRM (Salesforce, MS

Dynamics), visualization (e.g. Tableau) and management dashboarding solutions

(e.g. QlikView) in the right format and structure for further correlation analysis

by big data experts.

7 STEPS TO ….The steps to comprehensive multi-source feedback management may seem complex but with a bit of discipline and cross-organization involvement, the solution is rather easy to implement.1. Ensure that you are working with as rich data as possible.Background variables like customer identity, related demographics, and key purchase behaviors can be used as rules for effective distribution of insights to people in different organizational units and roles.2. Make sure the structure of all feedback data sets (i.e., feedback data from one source) is as uniform as possible.Many predictive analysis projects and real-time feedback management processes fail simply because each data set has a unique set of fields, which makes it difficult or impossible to compare the insights from multiple feedback sources. A uniform data structure can be pretty easily achieved using a few simple data scripts and macros and importing user, demographics and key purchase behaviors from other systems such as CRM.3. Automate the flow of data from feedback channels to the aggregation and analysis service.Because most operational insights lose value with time and uploading data manually requires discipline and resources, all data sources should be connected in real-time using, for example, REST or SOAP protocols.4. Choose an aggregation and analysis service that is capable of automatically analyzing free-form text feedback.Since most of the feedback data will be free-form text-based, an automatic, often multi-language text analysis functionality must be included. And customized ontologies need to be created to capture the differences between various industries and companies.5. Create a single “master” data set with all the feedback.All data that has a comparable structure should be aggregated to a master data set for top management, PR, marketing, and risk management purposes. In the master data set, the data source should be used as a new background variable.6. Create a dashboard user-interface in which people have access only to the exact data that is relevant for performing their specific tasks.People from different organization units, and functions have different data needs and don’t have time to sift through irrelevant data. An effective dashboard must allow rule-setting based on background variables or text analysis topics or sentiment.7. Enable more advanced, big-data analysis using visualization and management dashboard solutions.Make the analysis results available to third-party CRMs (Salesforce, MS Dynamics) as well as visualization (e.g. Tableau) and management dashboard solutions (e.g. QlikView) in the right format and structure for further correlation analysis by big-data experts.

INTERESTED?

PLEASE CONTACT US and Canada Stewart Nash stewart@etuma.comFrance Philippe Thenot philippe@etuma.comScandinavia Ilona Lahtinen ilona@etuma.comRest of Europe Loek van der Helm loek@etuma.com

FOR MORE DETAILSwww.etuma.com