At the market, Tajikistan, photo by Kate Dixon, 2008 (Source: Wikimedia Commons)
Ideas for Leaders #282

RET: Market Research in Real Time

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Key Concept

As market researchers cannot follow customers around 24 hours a day, how else can they understand what sways them to buy certain brands? This Idea discusses a new research tool — real-time experience tracking (RET) — which seeks to capture how people respond to experiences and interactions with a given brand, all in real-time.

Idea Summary

What drives customers’ attitudes and behaviours? This is the golden question for marketing executives, who often rely on data from surveys, focus groups, interviews, etc., in the hopes of trying to understand how to better influence their customers. But according to Emma Macdonald, Hugh Wilson and Umut Konuş, these types of data suffer from a fundamental flaw: they rely on customers’ memories, which wane rapidly. They propose that a new research tool can provide marketing executives with better answers: real-time experience tracking (RET).

Developed by market research agency MESH Planning, RET involves asking participating customers to take part in a quick SMS-based micro-survey every time they come across a given brand or one of its competitors. The survey requires them to input a four-character text message as follows:

  1. a letter indicating the brand involved;
  2. a second letter for the type of encounter (referred to as the ‘touchpoint’);
  3. a numerical score indicating how positive the customer feels about the encounter; and
  4. a final score for how persuasive the encounter was.

Their responses are displayed back to them in an online diary, where they can interact with their data, comment and upload photos. In addition, participants also fill out surveys at the start and end of the study to record brand attitude changes.

One of the primary benefits of RET is that because data is gathered in real time, it can be acted on in real time too. But also, valuable insight can be harnessed about all forms of brand communications, including mass communications, word-of-mouth, point-of-sale, brand usage, etc.

A number of leading companies have already been using RET to better guide their marketing decisions. PepsiCo, for example, used RET when it re-launched its drink, Gatorade, in Mexico. They planned to reposition the brand around sports nutrition and soon found that seeing Gatorade advertisements or seeing other people drinking Gatorade in gyms and parks were twice as effective in shifting brand attitudes as similar encounters elsewhere. Similarly, companies including Unilever, BSkyB, HP, Energizer and Microsoft have all used RET successfully.

Business Application

Firstly, it is important to ensure companies using RET obtain a balanced representative sample, for which potential respondents should be carefully profiled. The sample must not be overly skewed towards certain type of people, such as those that are particularly technological savvy or innovative.

Furthermore, a comprehensive list of touchpoint types should be included the SMS-based micro-surveys; these should cover direct encounters (e.g. sales visits, conversations with call centres, visits to the firm’s website, purchases, etc.) and indirect ones (e.g. contact with other customers, seeing the brand in the news, or interactions with the firm’s agents, distributors, or retailers, etc.). 

Over time, RET data can be used to identify not only what motivates customers to buy a particular brand most, but also how various touchpoints combine in a chain to influence customers’ decisions. Some of the useful analyses companies can conduct using RET data have been outlined by Macdonald, Wilson and Konuş as follows:

  • Key drivers: analyzing these can tell you which touchpoints are most closely correlated with individual customer behaviours, such as a request for more information or an actual purchase.
  • Competitive analysis: see how effective touchpoints are at driving behaviour and shaping attitudes relative to the touchpoints of your competitors.
  • Chain of touchpoints: RET data can indicate where chains of customer reactions might be broken; for example, the decision to go into a store might result from a conversation with a friend, and the act of visiting the store increases the chances of making a purchase. 
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Authors

Institutions

Source

Idea conceived

  • September 2012

Idea posted

  • December 2013

DOI number

10.13007/282

Subject

Real Time Analytics