Delivering 12x ROI for a Leading British Supermarket and Digital Retailer

We explain how TMAC's conversation and speech analytics software was used to analyse our client's data and provide invaluable improvements

How TMAC helped a nationwide supermarket to understand their demand using speech analytics

A supermarket and digital retailer came to TMAC with one key problem – they had tonnes of customer data and recorded calls, but how could they analyse it all to better understand their customers and the issues they faced? Better yet, how could this be automated so they could analyse future contact centre data with speed and accuracy so they could identify pain points before they grow?

By conducting upfront analysis of their data spanning across their existing channels, we were able to make some immediate cost-reductive and revenue-maximising recommendations. This occurred within the market-leading 4-week deployment period whilst we got their contact centre managers, leaders and agents set up with our conversation & speech analytics platform to actively monitor 100% of their demand going forward.

TMAC’s work

Using a mix of bottom-up language modelling and what we’ve seen across other client work, we created 47 contact driver categories and topic models to identify key themes throughout the data we were given.

From there, our Speech Analytics software was dispatched to review all the client’s data and test our hypotheses, exploring the causal relationship between these categories and call outcomes (sentiment, CSAT, purchase and churn) and establish an automated text analytics pipeline.

Our work focused on identifying opportunities to improve CX so our client could refocus contact centre agents to take these opportunities, with the goal of ultimately improving their brand reputation.

On top of the 47 contact driver categories and topic models that we initially created, we used further categories to analyse customer sentiment by contact type and created a data lake to house all of our clients previously unstructured data.

The results

For an initial £20k investment, TMAC helped to identify over £150k of operational benefit and roughly £100k of benefit through actionable automation and fulfilment improvements. Our analysis and suggested changes to their current system provided 12x ROI for our client.

  1. We identified that over 80% of contacts came through reasons that are either negative, unnecessary or non-value adding.
  2. The issues that lead to the highest number repeat of contact (and driving wasted operational costs) were damaged goods, a poor cancellations and refund process, and a lack of information regarding order status/stock product availability.
  3. An entire third of all contacts came from damaged goods, identifying an opportunity to improve the fulfilment handling process by holding third parties to account via claiming or a partnership changeover.
  4. Roughly 10% of contacts were due to product availability enquiries. These contacts were identified as a prime opportunity for automation and self-service for customers via chatbot demand deflection or visibility conditions based on stock refresh.
  5. ‘Cancellations Refund’ and ‘Need Proof of Purchase’ represented almost 25% of contacts – another significant opportunity for operational cost reduction.
  6. We identified a more specific problem with the process for customers buying on credit and then having to make returns, resulting in high levels of customer confusion and negative sentiment that led to “bill shocks” and hurt satisfaction scores – increasing likelihood of churn.

If you’re struggling with unstructured data start turning your data into insight with TMAC. Automatic conversation analytics can unlock 100% of your demand and reduce your reliance on untrustworthy random sampling.

Better yet, we have market-beating deployment (an average of just 4 weeks), and at just 20% of the cost of other providers.

Contact us today for a free demo and to discuss how we could boost your contact centre’s efficiency, analyse demand, and provide the ideal customer experience.

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