In the context of Artificial Intelligence age, appropriately analyzed data has been an essential ingredient to build & drive intelligence based digital products and service experience solutions. Enterprises like tier1 consumer retailers function on the basis of all kinds of intended customer’s data insights and make critical decisions to modernise customer experience accordingly. The insights which are drawn about their intended customers and how they interrelate phygitally (physical +digital) with their products and services are tactically scrutinized. The customer journey analytics provide companies a whole new level of insights into customer’s browsing, buying trends and complete 360 degree view of journey interactions. Moreover, it opens up incremental opportunities for brands to determine and amplify customer experience which led to customer stickiness.
Analysis of large and complex sets of data offers insightful information about consumer, competition and business. However, this information is quantitative in nature, assembled with particular anonymous data points and performance ratings. Not sure, how far analytics is successfully helping brands to plan and execute meaningful actions resulting in offering the personalized customer experience.
Actionable insights must help the Experience Re-Imagination team to craft aligned, relevant, contextual and specified solutions. If not, then there is a serious need to extract qualitative insights in combination with ethnography research and computational analysed data to make the solution rich, precise, comprehensive and futuristic from the customer and business standpoint.
In context of Ethnographic research, (a qualitative in-depth study method of human behaviour, context, ecosystem culture, beliefs, the discipline of anthropology), it involves empathetically inspecting of how and why things are like the way they are demonstrated as an info graphics or charts such as Sankey diagram, line chart, and bar chart in the analytics report. Hence, it is referred as Human Centred Data Science and Analysis. Off late, human centeredness is remarkably realized as a growing side for data analytics activity within consumer services sectors. The prominence of ethnographically researched insights, collection of quantified data and accurately manipulating it in the form of algorithm which is the key to success of data driven customer experience solutions.
On the other hand, leveraging data is not just to be competitive in the market but re-imagining customer’s interactive avenues, encounters and cross touch point journeys to create more engaging experience. The customer’s historical data points in the context of behaviours, preferences, likings, psychology, frustration, tipping moments, complaints, payment histories, usage patterns, feedback and end to end journey interactions with enterprise or brands has to be thoroughly studied, researched and concluded so to create transformative meaningful customer interactions and long lasting impressions. More better the harnessed data, more condensed will be the insights drawn and stronger decision making. Here's an article on how long should you keep your customer's data.
Appropriate Data analysis help companies/brands in co-creating a whole new level of perceived insights into customer behaviour trends. It significantly opens up the infinite chances not just to recover customer issues but also to keep customer constantly happy and engageable. A robust AI research framework along with human centric creative approach can certainly help in gathering qualitative and quantitative insights, formulate decisions and act on the informed insights resulting in more personalized customer experience. Nowadays, it is essential for companies/brands to differentiate by reimagining customer’s experience which involves more engaged customer, custom value propositions, emotional encounters, tailored choices; and proactively intelligent customer service interactions.
This article was originally published by him on LinkedIn.