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Using BI To Optimize Marketing For Increased ProfitsSubmitted by Esmart Fri, 21 Mar 2008
Once a business market enters a mature stage, the emphasis changes from customer acquisition to one of customer retention and increased revenue per customer.
This requires companies to know more about their customers at an individual, rather than a market level. Attempting to achieve this using traditional means would be cumbersome, expensive and take far too long. This is where Business Intelligence shines. The core value of BI capability is to analyse large volumes of data to extract those hidden gems that can turn marginally profitable services and customers into highly contributing revenue streams. The more customers a business has, the value BI can derive increases exponentially. Being able to identify your most profitable customers, was in the past more about guess work and subjective surveys than the laser targeted, logic driven capabilities of a business intelligence application. BI helps businesses understand customer regardless of the industry in which you operate. Consumer retailing, telecommunications, and financial services were early adopters of BI, and there are many case studies supporting the positive impact they had on the business. Typcial activities used by such companies to increase profits include:
Marketing Analysis Marketing analysis refers to analytical activities used to understand revenue generation fundamentals, such as:
With a well-structured BI environment, marketing analysis can be done in near real-time, providing fast feedback on current promotions or product launches, as well as indentifying long-term revenue trends. This helps marketing better understand the underlying drivers of revenue growth. Using better information, companies become more effective in attracting new customers, retaining profitable customers, and achieving sustainable revenue growth. By understanding the relationship between channels and profitability, targeted incentives can be introduced to drive customers towards more profitable channels, and early feedback allows adjustments to be made to promotions to increase marketing ROI. Customer Segmentation Business intelligence provides the capability to segment customers to greater levels of granularity. Micro-segmentation can be aligned with individual promotional offers for up-sell and cross-sell campaigns. This ability to substantially extend traditional customer segmentation allows businesses to gain greater insight into buyer behaviour. Previous consumer segmentation was limited to: Demographic segmentation - grouping customers by common characteristics such as age, income, occupation Geographic segmentation - grouping customers by where they lived, worked and/or shopped. Psychographic segmentation sought to group customers by such potentially common characteristics as personality, leisure activities, and values Business demographic segmentation - grouping customers by such characteristics as industry, role in the value chain, and revenues Regardless of the basis of segmentation, the connection between belonging to a particular segement and actual purchasing behavior was not clear. By using BI tools and techniques to mine data, relationships between various attributes could be identified, without any pre-conceived expectations. Whilst BI tools do not replace traditional segmentation and market research tools, they do provide more powerful with advanced capability to narrow segments, and better understand the needs and values of those segments. Using this information, products and services may be more targeted towards providing a closer match to identified needs and values or smaller groups. This results in improved conversion of offers, increased ARPU and greater profitability. Advertising, Direct Marketing, and PR Using BI driven market analysis and customer segmentation, a deeper understanding of customers helps clarify marketing messages used in advertising, direct marketing, and PR campaigns. Campaigns can be highly tuned to meet specific requirements, such as:
Real time BI can provide instant feedback on the impact the campaign message is having, and adjustments can be made to redirect failing campaigns, providing a better return on advertising budget. The level of granularity of such targeted advertising is unlimited. Specific purchasing behaviour of individual consumers can be identified. By only targeting those most likely to accept an offer, results in reduced campaign execution costs. Channel Management Sales channels vary by industry and position within the value chain:
In some cases, enterprises have expanded vertically to integrate channels inside the corporate arena. However, most companies must make strategic decisions as to what types of channels to use and which vendors within a given channel. BI can be used for channel analysis in similar ways as it does for customer analysis to gain insight into, for instance:
By integrating this performance data with channel cost information, channels can be optimized to become more cost-effective. CRM In BI, CRM means analyzing customer behaviour and sales force performance to identify opportunities to cross sell different product and service bundles. CRM helps companies better understand their customers and enable more effective marketing analysis and customer segmentation. Coupled with optimization of marketing and sales business processes, more effective revenue generation and revenue growth can be achieved. Category Management Large retail giants such as Wal-Mart have consolidated consumer product retailing,driving highly competitive strategies. Category management is one such strategy, where retailers are able to optimize contribution margin per cubic foot of retail shelf space. This is achieved by pushing inventory and shelf stocking costs onto suppliers, avoiding stock-outs, and allocating shelf space based on a combination of understanding customers purchasing habits and on knowing revenue and gross margin characteristics of each product and product category. BI provides advanced category management capability. Importing point-of-sale data into the BI environment, retailers can understand product-level demand trends and how they vary by relevant dimensions such as geography and service area demographics. Revenue lift with promotions can be identified and used to target customers based on past purchasing behaviour related to similar promotions. Using a combination of multidimensional demand trend data and the ability to track the effectiveness of promotions, retailers ensure they have the most profitable product mix on the shelves. Category management BI also can be used to optimize supply chain performance, further improving profits. Event Based Marketing An added impact of BI is the awareness a business gains of all the different interactions a customer has with their channels, direct sales teams, customer support and websites. Each interaction is regarded as an event, and an opportunity to gain further insight about the customer, the way they use your products and services, and their perception of the business. By analysing the current event in real time, individual offers can be customised and presented to the customer, during the event duration. Marketing Resource Management Marketing utilises a broad range of resources to manage customers, promotions, events etc. Using BI capabilities to improve processes surrounding these instances, helps to best utilise resources where sales margins are most profitable. Summary The above examples of how BI is used to improve revenue generation and profit are all based around analysis detailed and specific information about customers past purchasing behaviour. By gaining a better understand as to the needs, preferences and purchasing behaviour of customers, the business can become more effective at growing revenue and retaining profitable customers. And that means improved profit margins. About the Author
Gail La Grouw is consulting director of Coded-Vision Consulting, architects of optimal corporate and marketing performance management. She specialises in business intelligence and business performance technology
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