The curious case of isolated customer data

With an array of channels at their disposal, customers are more becoming more and more demanding and inclines towards retailers that offer maximum value and convenience at a lower cost.
Expectations are high and if you cannot meet them, they will move on and find another brand to lavish their time and money on. To put it straight, retails need to pay more attention and take proactive measures to deliver an experience the customer will want to return. A thorough knowledge of customer is therefore mandatory, as it has become essential to provide every customer with a very personalized experience.

The Problem

The customer was facing the challenge of maintaining quality for a highly configurable and customizable product lifecycle management platform. The platform was using latest technologies and was cloud agnostic, adding to the task of managing application lifecycle amidst short release cycles.
They needed a partner with expertise in managing enterprise grade applications and ability to comprehensively test and assure quality of their solution and future releases. Lack of process documentation added to the challenge.

Isolated customer data

The collection of customer data is scattered in legacy systems – with departments such as sales, marketing and customer service holding information in silos. In addition, information contained in sources such as social media, mobile apps, email, SMS, POS, coupons, loyalty programs etc. add to the barrage of data.
Silo-ed data makes it difficult for marketers to present the right experience that customers expect, as they are not able to tap into the whole picture of the customer journey.

Building a 360 degree customer view

Each journey has to start somewhere. The journey of creating a holistic view of your customers might start with getting the right technology in place, but it doesn’t end there. The focus now shifts to applying all that information. This is done in 4 basic steps:

  • Create A Unique Global Consumer ID – This includes information like whether someone is a member (or not), a new or returning customer, whether there’s any cross-brand integration going on, etc. Background data, such as regional and household information, is needed too.
  • Collate Internal Data – This step gathers info like transaction information, customer service details, and overall customer satisfaction. It also covers the customer’s activity on company websites, loyalty programs, and social media sites.
  • Collect External Data – During this phase, the attention shifts from customer and company to the outside world. We’re looking at category information, trends, and events; geographic and demographic profiles; general attitude and lifestyle information, and competition analysis.
  • Apply Predictive Analytics – With all available factors in the mix, we can start to forecast customers’ likelihood to purchase, pursuadableness, potential upsell and cross-sell effectiveness, and the conversion of prospective customer.

 

Optimizing your Holistic View of Customers


 


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