Case Studies

Case Studies

  • Industry: retail
  • Pain identified: Loyalty customers were not renewing in response to reminder calls to renew subscription
  • Solution: simple correlation between customer complaints and issues not resolved to be tackled first before carpet-bombing the whole base
  • Stepwise execution
    • Check for negative incidents
    • Outcall only those who have positive ratings of the service feedback for renewal
    • Outcall those who had negative feedback or requests . Solve the problems and then only request for renewal
  • Industry: retail
  • Pain identified: customers complained of product performance in the NPS feedback.
  • Solution: Quick red flag from detractors identified the batch and date of manufacturing. The product was removed off the shelf and the marketer was informed immediately. Customers who were sold the product were proactively called and action taken.
  • What worked: The customer who received the NPS rating SMS could write ‘why’ they considered the product below par. Since the ML directed the feedback direct from the customer to the quality team, they were able to know immediately and take action immediately.
  • Industry: B2B client in Supply chain / Logistics
  • Pain identified: Truck waiting to be unloaded spent too much time idling at the warehouse, delaying onward journey in an industry defined by time.
  • Solution: The customer warehousing teams were linked to the CRM and the notification helped warehouse teams to be proactively informed and ready as well as confirm receipt of delivery.

Industry: Telecom

Pain identified: Customer  calls the contact centre to understand the promotion so that they can take maximum benefit. Contact centre typically would provide generic information.

Opportunity: By linking customer usage history and also seasonality, was able to enrich information for the Service Executive. This meant that the executive was empowered to provide recommendation which they were now confident of being a better fit for that customer rather than ‘one size fits all’ sales spiel.

Step wise execution:

1. CRM was augmented with this data is provided account wise.

2. Training investments to uplift conversational with a proactive advisory rather than a reactive sales pitch tonality 

Outcome: 80%+ increase in conversions from inbound contact centre channels in 3 months of launch

Industry: Fashion Retail, ecommerce

Pain identified: The spiralling refunds and exchanges cost threaten to erode profitability. Companies are caught between CX ( execute lenient return policy) or pursue Profitability. 

Opportunity: Restricting returns and making them more difficult for customers will impact conversions and loyalty.  By impacting the avoidable reasons for return, company can improve CX, increase delight and lower the % returns.

Step wise execution:

1. Capture customer feedback more comprehensively

2. Focus on the biggest reason for return which is incorrect size 

3. Recognise the different needs of customers who buy for gifting and tailor communication accordingly.

Outcome: 15%+ reduction in returns due to size related issues by better understanding customer needs and updating communication and information accordingly.

Industry: Multi-sector Consumer Packaged Goods especially those having DTC ( Direct to Consumer) strategies.

Pain Identified: To build brand awareness and brand engagement and make an impact, it was difficult to quantify returns for every campaign.

Solution: Use of a SaaS AI platform a brand was able to input variables based on the segment needed for targeting which focussed the spends. Coupon codes were inserted and specific KPIs that reflected the goal were now measurable. 

Benefits : Better engagement, conversions could be tangibly measured and could now be set up for comparison for future campaigns. Differences in geographical and segment wise behaviour to the same content and messaging could now be fined tuned with more confidence.

(* Nett Promotor Score – Customer feedback)

Industry: Tech

Pain / Gap Identified: Besides complaints, the company was not able to understand the customer sentiment and perception holistically especially when after customer focussed investments were made. Therefore they needed guage the impact so as to direct further investments in Human and Technology investments.

Solution:  The Company rolled out the feedback form on a NPS Platform which was ML based and was able to refine text analytics as well as simple score trends for all it’s A Category customers within 3 months and after a year it was able to obtain clear ‘direct’ and ‘un-filtered’ customer feedback from Influencers, Decision Makers and Users within its Enterprise Clients.

Benefits : This enabled the Customer Focussed company to prioritise specific improvements ( whether in processes, policies or technology) based on feedback of rolled out initiatives as well as plan forthcoming initiatives based on actual customer needs.