Q&A: Transforming customer data into actionable insights

Data is the new gold, offering valuable insights into customer behaviour and actionable information for retailers, says Wynand Smit, CEO of INOVO.

Data is the new gold, offering valuable insights into customer behaviour and actionable information for retailers, says Wynand Smit, CEO of INOVO. Of course, that data has to be well managed by brands and retailers, Smit reiterates in our Q&A lead this week.

Which data set is the most difficult to manage?
Wynand Smit.

Today retailers receive an overwhelming amount of data from multiple points – in-store purchases, websites, SMS, WhatsApp, customer call centres, bots, social media and email. Voice traditionally faces the most challenges due to limited sampling capabilities and incomplete or unrepresentative datasets. Often retailers use manual sampling methods that capture a low percentage of interactions and use key performance indicators to assess the call quality. This type of quality assurance is often more focused on the agent, than on the customer or on identifying challenges. In addition, the speech transcription can cause delays and introduce errors. None of these vectors open up opportunities or potential new avenues of customer engagement.

What other challenges do retailers face in collecting data?

Customer-service surveys frequently only tackle a small percentage of customers and the information is limited. This constrains insights and decision-making. What’s needed is to sift through the data to help retailers improve their services, provide returns, or deliver measurable benefits. The problem is that there’s a large volume of data that can be difficult to store or extract meaningful insights from.

So, what would you recommend?

What’s needed is for retailers to unpack precisely what’s happening in interactions – using keywords and phrases to identify specific trends, types of interactions and engagement parameters. This approach will help to whittle down the conversational value into key metrics that allow for relevant decision-making. For example, if a speech-analytics solution picks up that there’s a need for more extensive agent training, then the retailer can train agents better who in turn can engage with customers better. This often results in the benefits of upselling, reselling and customer retention.

Does voice-data collection take emotions into account?

Yes, data collection for voice monitors positive and negative emotions. Drilling down into this information shows if there’s a trend with a specific agent, product or query. This then helps the retailer refine those specific processes and clear out any bottlenecks that may have hampered sales or retention. In addition, the data can be correlated with specific sales, which allows the business to then connect the virtual dots and translate calls into sales.

What about sales data?

Sales figures can reflect internal and external trends. This data can, for example, show a dip in product-order volumes that correlate to competitor cost-cutting. The reason this is of immediate importance to the retailer, is that they can then adjust their pricing to recapture the market and potentially open up new growth opportunities.

What implications does this have for customer call centres?

By analysing customer interactions, retailers can effectively reshape how their contact centres engage with customers. They can use the data to refine product offerings. They can also identify key trends to adapt services or improve agent training in order to boost upselling or cross-selling. Lastly, it can help minimise negative interactions and improve the overall customer experience.


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