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Croma: Marketing Analytics in Electronics Retail

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Cromā: Marketing Analytics in Electronics Retail

Croma is a Tata Enterprise, that sells consumer electronic goods and accessories at three touchpoints- mobile, online and brick and mortar (large real-estate spaces) stores across India.

Croma is run by Infiniti Retail which is a 100% subsidiary of Tata Sons. Their competitors in the online market are Flipkart, Amazon and Snapdeal while their physical space is challenged by Next Retail and Vijay Sales that has a stronghold in West and parts of South India.

With presence in both offline and online space, it became a big challenge and therefore an opportunity to create synergy between the two. With that objective in mind, Infiniti Retail has partnered with Infinite Analytics – an MIT backed Data Analytics company to understand consumer behavior, identify consumer and product segments, achieve personalization for individual consumers and, develop product and consumer catalogues. (Analytics India Magazine, 2014)

Meanwhile, a sister Tata Company, TATA IQ is also running simultaneous analysis of its extensive database to create a loyalty programme for its consumers across the various Tata Group companies. As Croma Retail is one of the group’s consumer facing companies, it has been roped in to develop the programme. This is really Big Data we are talking about. The TATA conglomerate is worth combined a whopping $130 Billion. (Mandavia, 2017)

While the latter is a business development process and still underway, the former partnership between Croma and Infinite Analytics has begun to show results. Conversions went up 217%, revenue share up by almost 25% and 28.8% spike in order with recommendations.

Tools being used at Croma for Marketing Analytics

  1. SAP Digital Consumer Insight
  2. SAS Forecast
  3. Hadoop
  4. Python
  5. Machine Learning, Natural Language Processing
  6. IAN- Artificial Intelligence

Using Marketing Analytics to achieve Personalization @ Croma

Croma has put a lot of focus on understanding consumer behaviour through analytics. They wanted to identify individual consumers and treat them as segments of 1. The picture below describes how they brought customers browsing online to walk in their stores and increase their CRR and footfalls in stores that were not performing well.

This synergy from the online to the offline is how they have managed to stay ahead of their traditional and e-commerce competitors. They talked to consumers to figure out what each of them wants and offered customized schemes and discounts to them.

[pic 1]

Picture 1: The journey of personalization with optimization.

A/B Testing and Manual Experiments

This is a tool used to determine tendencies and post-purchase behaviours. These are descriptive analytics typically determined by functionality requirements.

Insight 1:

Significant percentage of consumers close purchase in one session.

Feature:

Stock Running Out messages on product pages to prompt consumers to buy before they leave the website.

Result:

Increase in Conversion rate by 100%

Insight 2:

High bounce rate for Out of Stock pages

Feature:

Product recommendation pops up on OOS pages

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