When used for analysing the growing mountains of customer review feedback and NPS and the more intelligence you give it upfront the faster, more accurate and consistent the results will be.
Recent research that I have been reading indicates that 70% of people will leave an online review about a business if asked. 92% of customers now read online reviews & 40% of those form an opinion about buying something from reading just 3 online reviews. Customers are increasingly giving feedback and finding reviews useful.
So what does this mean if you are working in customer experience receiving all this feedback from customers? More to the point, what are your going to do about it. Something or nothing?
My own experiences of giving feedback over the years are mixed. So often you give the feedback but feel that absolutely nothing is being done about it. For example every time I contact my mobile phone company they ask for feedback by text with 3 fixed questions about my recent experience and then a free form field for why I gave the responses I gave. Every time without fail I respond (usually frustrated and angry because of the service I receive) but I feel that nothing ever happens with my feedback. No one ever gets in touch to find out more, or to ask what could have been done to improve my experience or even to say sorry we messed up. It would be lovely if just occasionally I got a text saying thanks for your feedback we understand your pain and are working on it..... Now I appreciate that my mobile phone company probably has huge volumes of frustrated customers all of which would appreciate being treated a little bit more like individuals and less like an inconvenience but please, please, please don't ask me for my feedback if you aren't going to do anything with it.
If you are getting high volumes of customer feedback it is critical to analyse it as quickly as possible to be able to do something about problems and work on getting your customer experiences right and to be able to tell your customers that you are doing something to address their challenges. The volume of reviews about your business across multiple channels is increasing all the time and sometimes the volume of data just can't be easily managed.
Using Artificial Intelligence rather than teams of analysts for analysing your growing mountains of customer review feedback and net promoter scores has a number of huge business benefits:
- Time – AI can identify anomalies early therefore enabling problems to be fixed quickly. So if there is a sudden surge across all channels in complaints about something, this can be identified immediately (often before your analysts will even notice there is a problem) and decisions can be made in short shrift that ensure any increase in complaints stops before they generate negative review and cause major damage to brand reputation or business. Getting on top of customer complaints and solving them quickly improves overall customer loyalty and retention. Relying on teams of people to do this analysis in a timely fashion is no longer necessary, AI is faster and better.
- Accuracy – the devil is often in the detail and a trained AI platform will be able to get to the bottom of customer review details and can identify solutions from the huge volumes of feedback from across multiple channels. What really lies behind your NPS results over time? Teams of analysts can do this work but there is often delays in getting data from various channels, the data comes in many formats which means time is needed to standardise it and often the detail gets lost in the overall weight of data. Clever customer feedback AI sifts through all the data in different formats, all the different uses of language that mean the same things, all the industry specific terminology, all the details without losing the nuances.
- Consistency – because customers tend to make feedback through different channels depending on their preference, convenience and anticipated response times the quality of the response has to be consistent – regardless. Again because data comes in different formats from different channels delivering a consistent response can be difficult. The use of AI for analysing customer feedback and making recommendations ensures consistency in quality of responses whatever the channel, it also can be trained to deliver consistent responses whatever the business, sector, language, down to product detail level.
- Cost – using AI instead of teams of expensive analysts will save money, brand reputation, improve customer loyalty, resulting in better NPS
All this is great, but businesses, industries and sectors use different language and terminology to do their business, which means that a standard off the shelf AI solution won’t be as accurate or consistent in its analysis.
In our experience, for the fastest, most accurate and consistent customer feedback intelligence it is necessary to build specific models that tailored to your unique business environment that recognise industry, sector and business specific language that your customers might use in their feedback that is unique. This delivers better understanding of customer sentiment and ensures greater accuracy of the analysis and consistency in response across all channels. To achieve this requires flexibility in your customer feedback measurement system to be able to adapt to your specific business environment, many solutions are not able to do this in a timely fashion however the SentiSum Insight as a Service solution comes with industry ready models pre-built with all the intelligence to achieve fast, accurate, consistent results that will improve customer reviews, NPS and feedback, brand reputation at lower cost to the business.