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The future of CXM

The future of CXM 40

The future of CXM 41By Michalis Michael, CEO of DMR

Any predictions about the future of Customer Experience Management (CXM) need to take into account the simple fact that all customer interactions – irrespective of source or language – will be available for analysis.

This isn’t a speculative prediction, but a simple extrapolation of the fact that the technology is already available.

Source and language agnosticism is swiftly becoming the norm in the world of listening to customers, backed by robust artificial intelligence (AI) capable of assessing enormous and largely unprecedented quantities of customer data and capturing mostly the unsolicited and sometimes the solicited opinions that customers produce by the millions.

As CXM professionals start coming to terms with the implications of this technology, the future of the field will be characterised by both the challenges and opportunities that come hand in hand with a universal approach to hearing and understanding all customer interactions without exception. No more reliance on samples of customer feedback.

New forms of KPI tracking

One of the more obvious – and potentially impactful – aspects of CXM that will be affected by access to all customer opinion is tracking of multiple relevant KPIs.

Most companies currently just track the Net Promoter Score (NPS), which for some time has been used to get a sense of customer loyalty and satisfaction by asking customers to indicate, on a scale of 0-10, their likelihood of recommending a brand to friends and colleagues. Respondents can then be categorised as detractors, promotors, or passives depending on their position on the scale.

The resultant calculation provides CXM professionals with a simple, single figure – and while reaching for an easy-to-articulate score is commendable, this single KPI tracking just won’t reflect the nuance and comprehensiveness provided by technology that can hear every customer interaction.

What, then, does the future hold?

I think we’ll inevitably see the increased prevalence of multiple, composite KPIs created by synthesizing several different customer interaction sources.

Rather than merely asking a small sample of people for their opinion (an opinion that could be selected at random or fabricated), it will become standard practice to integrate sentiment, purchase intent, social media engagement ratios, and so on.

That doesn’t mean CXM professionals won’t find ways to present these findings in a single figure – e.g. DMR’s Net Sentiment Score (NSS) and Social Presence Score (SPS) – but it does mean ensuring that the measurement of market performance needs to operate on the basis of sophistication commensurate with the breadth and variety of available data.

Finger-snap pain point resolutions

Of course, this kind of data can do more than indicate a company’s market position – it can equally be used to improve pain point solutions on both a proactive and reactive level, and the future of CXM will be shaped by the speed and efficacy with which those pain points can be addressed.

After all, with any and all customer interactions at your disposal, it will become increasingly common to not only find and rank pain points in order of priority, taking into account customer journey stages, but devise robust mitigators that strike at the heart of a given problem.

Reactively, this will likely involve targeted workflow-based solutions – perhaps by ensuring that call centre staff and complaints departments are able to use guidelines for empathetic responses to customers calling about a problem. And, with the right data fusion and integration, reactive workflows will be dynamically adaptive, changing to suit new information.

Similarly, proactive solutions – those that relate to some form of operational fix – will likely be created and carried out in real time. And it goes without saying that these more sophisticated solutions to customer pain points can only serve to limit churn and improve customer retention.

It’s worth reiterating that these are confident predictions for the simple reason that these outcomes are already possible. All that’s required is for organisations to invest in the specialist help and technology needed to turn myriad existing customer opinions into actionable information for improving CX.

Once the pain points are addressed and the customer churn and retention is optimised the next order of business is to leverage gain points or strengths, but this is a subject for another article.

AI annotation accuracy

This reliance on newer technology will come with its own set of caveats, however.

Given that CXM professionals will be increasingly dependent on AI to find and – crucially – annotate customer opinion for factors like sentiment and purchase intent, they are going to take a great deal of interest in the annotation accuracy of their technology.

Of course, it’s no bad thing whatsoever to ensure that the analysis of millions of interactions across any language in a matter of seconds is built upon a strong and accurate foundation.

As the CXM industry evolves to embrace such technology, we’re likely to see the beginning of a virtuous circle in which the need for comprehensive analysis is met by all the more accurate annotation, which in turn will only augment the possibilities of CXM – resulting, no doubt, in strong growth prospects for businesses and a more satisfying experience for customers everywhere.

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