How proper data management will benefit your planning
By Ken Nyadimo
Effective customer relationships are the lifeblood of any enterprise. Yet, many do a shoddy job in nurturing, prodding and skimming their market resources to achieve brand loyalty and drive up sales at negligible cost.
Such are the findings of joint studies undertaken by the CMO Council over the last three months.
One area in which attention is hardly paid is market data analysis and integration.
Revolutionary corporate thinking argues that strategic marketing is more of a study of behavioural dynamics that aim at influencing consumption routines and brand affiliations over time.
Subsequently, cut-edge technology should employ mathematical simulations to identify the range of applicability of coefficients in managing these dynamics into a profitability paradigm that may predict key financials ten years into the future!
As such, customer analytics, including insights into needs, wants, lifestyles, degree of involvement in brand co-creation, and consumption history, provide the foundation for brand equity. And brand equity means less competition and more profitability.
Yet in the typical scenario, product activities are the preserve of sales agents whose main interest is the heaving up of numbers at the counters.
Whether such buying activity sustains is never the immediate preoccupation.
Therefore, it is high time market planners made an effective presence at key transaction points to leverage psycho-economic data for greater business management.
Proper insights enable the devolution of practical intelligence into the understanding of specific dimensions of a current or future brand.
Given the difficulty of recurrently segmenting a market due to the high cost of effective research and advertising, good and intelligent data management is invariably a key point of advantage.
For instance, opportunities for multiple and inexhaustible cross and up-sells abound.
Increasingly, successful companies will look into new concepts like experiential communication and value-exchange.
As far as planning data is concerned, there is need for a good understanding of the implications of new management direction. Essentially, marketing and information technology must merge into a common engagement.
Secondly, corporate management must fully resolve dysfunctional intra-departmental conflicts that result in inadequate (or skewed) processing, development and relaying of key data for market and business planning (hence the ubiquitous weak or unsustainable profit centres).
Thirdly, information systems must now focus on customer data integration rather than bottleneck transactional histo-graphics.
And why does brand loyalty remain a difficult achievement for almost all major enterprises? The answer is firms are never worried about the lost customers, but are decidedly focussed on customer acquisition.
It does not matter who is lost, but rather how many customers there are at the end of the day.
Are there tools to measure the marginal importance of the churn? Definitely not much to talk about, going by the findings of related surveys.
In a similar take, a co-operative research early this year co-sponsored by the Computer Sciences Corporation, the Dun & Bradsheet consultancy and IBM provided me with stronger convictions about the implications of churn or lost "customership".
This is more so when you introduce concepts like cumulative hysteresis, adopters, imitators and initiators. Or when you do a forensic evaluation of firms that years ago controlled huge markets but are now either bust or extinct.
I have drawn interesting conclusions thereafter. For example, not many, including the "leading" firms, have fully comprehended the value of consumer insights, tempering most costly activities around pricing and placement.
Misplaced ROI bases on block constituencies, implying that subsequent analysis of data therein will yield nothing of value in as far as planning is concerned.
So in many an instance, it has been impossible to process data extracted from marketing planning systems for the simple reason that a cause-effect relationship is almost difficult to quantify.
If systems present you with a similar figure of the size of buyers at the beginning and at the end of the year, there is no data.
However, if there is a specific breakdown of this data into key integrals, then you may realise that even though the market size is unchanged, there have been movements in the individual membership of the segments.
The latter case allows great leeway for analysis because of its larger assimilation of data integration. As they say, it may appear similar but, actually, it is all different!
The emphasis on the relevance of data emerges from the belief that real customer intelligence arises from the tripartite relationship in customer information integration, customer insight development (through segmentation and modelling) and the strategic employment of such insights into planning.
It follows then that certain processes should now be included for the purpose of effective market data analysis and integration.
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