By Hadrian J Sammut
From Collection to Aggregation
Business organisations have been collecting customer data since time immemorial; whether on clay tablets, papyrus and subsequently paper. With the advent of computerisation most business organisations found themselves maintaining electronic systems designed and built to store and accumulate ever-growing amounts of raw customer data. Due to the way computer applications were then designed, it was not always easy to aggregate different systems, and the data they respectively stored, in an attempt to construct a single, unified, view of the customer.
All this has changed today; mainly through the emergence of powerful Business Intelligence (BI) analytic tools capable of reading across diverse and dissimilar business systems and applications. Such tools not only aggregate distributed data, but are also capable of carrying out complex analysis of customer behaviour and performance. It therefore comes as no surprise to note how most business organisations are today using BI analytic tools as the vital core of their profitable relationship marketing strategy.
The BI Analytic Tool implementation maturity
An effective relationship marketing strategy combines a reliable and dependable BI analytic tool in joint operational combination with a serious business insight. The BI analytic tool provides meaningful insights into corporate operations, which insights induce enquiries about the various affecting operational factors ‘hidden’ within the insight. Within this scenario, the BI analytic tool presents the initial analytical insight and the same tool is then utilised to ‘drill-down’ into the underlying factors.
Contrary to general opinion, utilising a BI analytic tool and using it to carry out analytical analysis is much more than mere ‘number crunching’ or even churning out of reports. BI analytic tools exploit available data, amalgamate it to provide homogeneity and then add context, value and focused meaning. Such an approach transforms micro-level client data into actionable information, enabling forward-thinking and predictive insights for better decision-making as well as the drive behind a stronger relationship marketing strategy.
The implementation of a BI analytic tool by a business organisation tends to undergo a progressive maturity as the application starts being used to address ever more complex requirements. The initial stage is generally a preliminary insight into the newly-aggregated customer data originating from across multiple applications. The next stage is often the production of straightforward Key Performance Indicators (KPIs) using the same aggregated customer data. At this stage business organisations will appreciate better, the potential of the BI analytic tool for the organisation and initiate a relationship marketing strategy that exploits the value of the data within the various business applications.
Establishing Critical Business Metrics
The BI analytic tools, when used within a relationship marketing strategy, could regularly review business performance trends and suggest actionable recommendations, enabling the organisation to consistently optimise the strategic marketing approach. In this way, organisations which invest in a BI analytic tool benefit from measurable, interactive, marketing initiatives that strengthen customer relationships, advance client intelligence, and maximise Return on Investment (ROI).
The tool could facilitate the identification of:
- the organisation’s most profitable clients;
- the top clients by specific product/service, product/service type or even over a period of time, in order to evaluate the varying level of care and consideration warranted by each group of clients;
- the best methods and channels with which to maintain customer loyalty in the most cost-effective manner possible;
- how to consistently deliver the right communications, incentives and opportunities that keep individual clients committed to an organisation;
- the inducements that best induce desired behaviours within clients;
- the most effective marketing tactics based on specific marketing goal;
- the clients who are prime candidates for cross-promotion of other products or services;
- current clients who demonstrate a high probability and potential of multiple purchases of different products and services;
- current clients who respond strongest to new offerings and ranking them as early adopters, opinion leaders and/or trial enthusiasts who will quickly purchase, spread awareness of, and increase advocacy for new products or services.
Conclusion
BI analytic tools utilise a data-driven analytic approach to help business organisations gain a unique understanding of client ‘value level’ as well a ‘value potential’ over time and according to the respective segment.
Such an intelligence insight allows companies to build and maintain stronger, direct, relationships with their clients. Such relationships can be used to ‘migrate’ clients’ lifetime values from less profitable to more profitable. Moreover, it helps organisations to forecast different client behaviours in order to attempt to change undesirable behaviour or catalyse desirable behaviour. Other organisations use BI analytic tools to monitor client defection, consumer longevity, up-sell and cross-sell opportunities, likelihood to respond, best customer acquisition, and much more. In fact, the only possible limitation is the probably the business organisations’ level of creative thinking.
