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Isolating Peak-Moments In Customer Journeys Using Contextual AI

The ‘Journey of Consumers’ has changed courses too frequently over the last half a decade – the frequency of change posing challenges for business owners and marketing think-tanks alike. This is in sharp contrast to relatively stable consumer journeys not long ago, which had a familiar and easy to understand linear shape – that was until the advent of  – Mobility devices, Location-based shopping options, Ability to transact seamlessly across channels, Recommendation Engines and Product and Service review mechanism to name a few.

As the consumers adapt to the new push-and-pulls of the shifting business realm, so does the peak moments along their journeys – the tipping point where they are most likely to get sentimentally hooked to the brand. These supercharged emotional occasions can ignite compelling consumer reactions and hence present sweet-spots of engagement between the brands and the consumers. Examples of these peak moments along a customer’s journey can be…

~ Discovery of an exciting new protein drink on the shelf for a customer who is into body building…the product being endorsed by Mr. Universe.

~ A handwritten thank-you note along with a free sample when a customer unboxes a new product.

“When graduations shifted from formal, large-scale ceremonies to at-home, family celebrations, Krispy Kreme offered each 2020 graduate a dozen specially decorated doughnuts for free. With that promotion, the company connected its brand with an emotional event that may not have been a key occasion for doughnuts prior to the pandemic.”

At the centre of this consumer-insight-culture are a few questions aligned with consumer-centricity…

  •  How nimble-footed an organization is in capturing and processing the data sets around its customers?
  • What has been the level of trust established between the consumers and the brand(s)?
  • Is the consumer insight framework privacy compliant?
  • Is there a direct communication between the consumers and the brand(s) when it comes to sharing of consumers’ behavioral data?

The answer to the above questions helps companies deliver contextual AI models, thus help understand ‘Consumers’ association of a certain behavior with a particular context’ – with the behavior becoming second habit for consumers.

The above dots, when connected help companies isolate the ‘contextual cues’ that drive the behaviors (more consumers are keeping hand sanitizer and disinfecting wipes near entryways for easy access and as a reminder to keep hands and surfaces clean). The contextual cues are an outcome of  Buy-stage and Life-stage analysis within the contextual AI framework.

[Life-stage Analysis + Buy-stage Analysis] –> Contextual Cues –> Peak Moments –> Second habits –> Loyalty

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