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Technologies to improve Customer Centricity

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Technologies to improve customer centricityWith all the talk and hype around technology and the benefits it provides, which supposedly must be capitalised on for organisations to remain competitive, organisations have to focus even more on the customer to stay competitive. How many organisations really utilise their tech to be more customer centric?

According to a survey undertaken by Gartner*, 89% of respondents believed that customer experience will be a primary basis for competition by 2016. This, in my opinion, proves that the customer is still critically important to any business – so the adage that ‘customer is king’ still remains true. So to my mind, businesses need to utilise their technologies better in order to pay more attention to their customer’s actual needs, if they want to remain competitive and relevant in the years to come.

Note that I am referring to customer in the broadest sense here – and in any field. So in the healthcare world, it’s the patient; in government, it’s the citizen; in sports, it’s the spectator, and so on.

Yesteryear it meant knowing your customer’s name, having a good understanding of his needs, shaking his hand, asking how his wife and children are doing, by name, and so on. Nowadays, of course, getting this right means turning to technology, where businesses have to make good use of their data, and the technologies used to manage such data. With respect to customer centricity, in addition to CRM, which we’re not going to cover here, three technologies stand out, namely unstructured data management, master data management (MDM) and customer analytics.

Data

It is estimated that 2.5 Quintillion bytes of data is created every day**. That is a massive amount of data, and based on this, I think it is safe to assume that almost all organisations have data on their customers. So the big challenge is not about getting data, but how to make sense of it and use it to your organisation’s advantage.

Some of this data is “standard” structured data that is created and managed in our transactional systems, CRM tools and so forth. That is relatively easy to be cleansed, processed, analysed and used by the businesses to get to know the customers better. However surprisingly few organisations even do this to their full advantage to understand their customers’ needs and wants, and, in so doing, offer their customers the type of service or product they require.

Then, enter unstructured data – call it big data if you must. There is a lot to learn about the customer from unstructured data sources, such as:

  • analysing email interactions;
  • determining their sentiment towards the organisation or the brand from social media feeds; through to
  • interpreting their emotions by decoding and analysing call centre interactions.

But in order to do that, a larger and way more complex class of data needs to be collected and managed. Now it’s one thing collecting emails, twitter feeds and call centre recordings, as per the example, but it’s a totally different kettle of fish categorising and indexing that lot, transcribing it and applying textual disambiguation to make sense of it all – and then transforming these newfound insights into a more structured form of data that can be utilised by analytical tools. It’s not the big data storage technologies that are crucial; it’s the text analysis, indexing, metadata dictionary cataloguing and text analytics technologies that are crucial.

Master Data Management (MDM)

Considering the fact that most businesses have, or hold, data about their customers, means that they can turn to MDM for support. According to Gartner, MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, consistency, and accountability of the shared master data assets of an organisation. In other words, MDM is about getting a business’s data in shape, as it provides a common language, to all the data, which a business deals with.

Now many people think MDM only applies to semi-static reference data, such as the list of postal codes, the list of product return reasons, the list of staff positions and so on. However, true MDM covers a much bigger, wider and dynamic set of data – in essence any data that is shared among applications. Examples include:

  • the hierarchy of accounts;
  • the list of our stores or service locations;
  •  the employee staff list;
  • the dynamic set of products and services we provide; and of course
  • the dynamic group of households, families and individuals we call our customers.

So “real” MDM is an enabling technology that can assist your organisation to get to and then properly manage a more complete “structured” view of the customer.

Customer analytics

Lastly, let’s look at customer analytics, which is the process whereby data (about and/or produced by the customer) is analysed by the business in order to get to new insights about the customer. This is what we use, of ten in conjunction with structured unstructured data, to get that wider 360-degree of the customer. Customer analytics provide us with those insights that help to get to know the customers better, and in doing so offer the opportunity to make more informed decisions around their actual needs or wants. Often times, customer analytics are used to identify and define new marketing strategies, as well as a more direct marketing approach – given the insight it delivers around customer patterns, and requirements.

There is also a big shift to the “segment of one”, where customer analytics aren’t used to identify groups of similar customers anymore, but where marketing messages and promotions are being designed “on the fly” to address the particular needs and sentiments of individuals at a particular point in time.

Concluding remarks

Imagine being the customer and receiving information about a product or service that you require at that particular time, given the circumstances you find yourself in – without having to ask for it. This is real customer service and will redefine your experience with a brand or business. Of course one has to be very careful that such insights to not come across as intrusive, creepy or overstepping some social privacy boundaries. Therefore, one has to be thoughtful about what data a business wants to or should be studying – and determine the why of it all – and carefully selecting data and analytics that are relevant to meet the overall business objectives – which will then produce the best positive results.

So when utilised together, unstructured data, MDM and customer analytics can offer businesses real opportunities – opportunities based on new insights, to make the right decisions at the right time – and thereby solidifying true customer experience and subsequently giving the organisation a competitive advantage going forward.

 References:

* http://www.gartner.com/smarterwithgartner/test/

**http://www.vcloudnews.com/every-day-big-data-statistics-2-5-quintillion-bytes-of-data-created-daily/

 

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