Archive for the ‘Customer Relationship Management’ Category
In a special Business Surgery, Carol-Ann Morgan discusses why Greg Smiths letter published in the New York Times (“Why I Am Leaving Goldman Sachs” – NY Times – 14.3.12 ) should serve as a warning shot across the boughs for any company which considers its customers or clients only in revenue generation terms.
A simple fact that is easy to forget amid the pressures of business success; but forget this at your peril.
Some key facts which provide ample justification for a customer centric business approach:
Customer centricity tends to fall in and out of fashion, but it is now most definitely “in”. Customer Experience Management is, in fact, the new buzz phrase. Savvy companies are delving further into the customer experience; placing it at the heart of all they do. With this there has been a flourish of tools, techniques, processes and people who are there to offer their services.
Bernd Schmitt’s book “Customer Experience Management: A Revolutionary Approach to Connecting with your Customers” makes a very interesting read indeed, from the perspective of a professional and as a customer myself. The stages he takes you through cause you to examine your own customer experiences from the on-going relationships, eg with banks and utility companies to the regular, occasional or “one off” retail experiences with the likes of Tesco, John Lewis and Hobbs.
Schmitt, essentially advocates a paradigm shift from the traditional functional – transactional approaches to marketing (citing Kotler’s work), towards one which takes account of the “experience” of being a customer, from cradle to grave (however long that might be). He argues a need to take the customer seriously; to recognise customers as assets of a business, without whom the company would not exist and worthy of boardroom consideration and respect.
Schmitt’s 5 steps towards Customer Experience Management:
Greg Smith states clearly the linkage between the values of the firm, where it positions the customer and the degree of engagement he feels with it.
Companies embarking on a journey of Customer Experience Management need to understand that it has to be a cultural shift across the organisation. It needs to be led by example, from the top, engaging employees in the movement to place the customer at the heart of how the company goes about its business.
This week, Kyle Cockett takes a look at the growing trend of ‘big data’ in the research industry, and the potential future implications.
During my tenure as a Research Executive, I have found myself working with a growing number of data sources during quantitative research projects. With a growing appetite for actionable insights, I increasingly find myself working in partnership with clients to source internal data that will help to provide quantifiable and conclusive findings. The process of harnessing such data is becoming progressively easier due to the increasing number of clients with well managed CRM systems in place. Coupled with the quantity of data shared on social media sources – regardless of the ongoing ethical debate – this means there is often an abundance of data to be examined and analysed during the reporting stage of projects.
The ever expanding size of datasets is not a new phenomenon – datasets characterised by large amounts of complex data from disparate sources have been around for many years. Tesco are often cited as one of the forerunners of large scale data mining with their Clubcard scheme, which gathers data on the purchasing habits of millions of customers. Despite this, only recently has the term ‘big data’ risen to prominence within the industry to describe such datasets, perhaps prompted by the ever increasing number of data sources – social media, smartphones and blogs are just a few examples of relatively new data streams. Google Trends reveals that the use of the term ‘big data’ has been growing in use exponentially in the past few years – and it is expected to grow even further. Ray Poynter, of Vision Critical, positions big data as the ‘one big trend’ at the forefront of the market research industry, ahead of twelve other multiple strands of expected change. As Poynter indicates, this prediction is firmly backed by the latest industry reports:
This does not necessarily mean the end of traditional quantitative research techniques, such as telephone surveys. However, it is expected that the findings from such surveys will increasingly begin to be used in conjunction with data from other sources – they will become one of the many scores or metrics fed into the big dataset. This is not expected to be an easy transition – many researchers currently work with data that has a size in the order of megabytes, while most big datasets are in the order of terabytes or even greater. Poynter states a belief that the move towards big data will be a ‘bumpy and a not altogether pleasant one for many market researchers’. If this is the case, then what is the benefit of gathering such large data sets? According to a research report by McKinsey Global Institute, big data is:
In order to conquer this frontier, it is essential that clients exploit the full potential of big data – the rise of big data provides huge scope for actionable insight and predictive modelling. Through the use of big data analytics, it is possible to create models that can predict changes in revenue, develop targeted customer value propositions, develop advanced segments, and identify where to focus resources among customers amongst other possibilities. There are many examples of such data mining already present in the retail industry – Tesco has a successful strategy of sending targeted discount vouchers to customers based on their typical basket of goods, while many online retailers offer purchase recommendations based on the past purchase history of their customers. These personalised touches often give retailers the extra edge over their next best rival. Applications are not always limited to customer satisfaction or retention either – by developing bespoke offerings, businesses can extract the full willingness to pay from their customers by accurately targeting premium offerings to appropriate segments. McKinsey estimate that a retailer using big data has the potential to increase operating margins by 60 per cent.
While many of these examples are heavily focused on retail, big data analytics also have the potential to shift approaches in business to business markets. Though B2B companies do not have the potential to mine data from social media sources as consumer companies do, they often still have well developed CRM systems that can provide a wealth of information on their customers. Who knows, it may take only one extra measure to provide insight that leads to a competitive edge?
To find out more about how we can extract insight from your big data, click here.