Who is your customer? It is a deceptively complex question that a surprising number of B2B companies cannot answer. The difficulty stems from several causes:
- Inconsistent definitions for customer attributes (account name, industry, segment, organizational hierarchy, contact name/email, etc.)
- Fragmentation of the data across multiple databases and applications
- Departmental perspectives on customer relationships
- Lack of an enterprise customer data management approach
The impact of all this is a severe slow down in decision making and an inability to optimize critical processes in customer facing functions, most poignantly in marketing and sales. The solution is to define customer creation as an enterprise process – not something that happens only in marketing and/or sales – and the implementation of data standards and governance to support it. This enables marketing to be data driven, but there are four distinct stages of data driven marketing and not all of them lead to success:
1. Stage One – Fast Failure. This stage is characterized by response-based decision making. Marketing decisions are based on response data from marketing systems – web hits, landing page registrations, and myriads of other campaign performance data. All of this is important, but leaves marketing unable to tie any of its activities to key business metrics such as revenue performance.
2. Stage Two – Slow Failure. This stage is introduces conversion-based decision making. Marketing and sales systems are integrated along with customer data definitions and structures. This provides a quantum leap forward for both sales and marketing. However, marketing is still one degree of separation from linking its activities to business performance. Sales pipeline is a good proxy but it is no substitute for the critical business data that comes from the next two stages.
3. Stage Three – Measurable Success. At this stage marketing finally is able to measure contribution to revenue. However, it is not enough to rely on initial contract data alone. Account A that closed for $1 million and account B that also closed for $1 million may be very different in terms of margin and lifetime value. Account A may have cost $250,000 to sell, install, and support where account B cost $500,000. If that's the end of the data set, then of course marketing should bring on more account A profiles.
4. Stage Four – Market Mastery. At this stage marketing understands the long term profitability of customer relationships. If over time account A buys nothing more and account B upgrades and expands its investment by millions of dollars at improving margins, marketing can refine its activities accordingly and begin to drive overall business performance.
The key lesson is that marketing is greatly influenced by the depth of data available to it. At each stage in IDC's data driven marketing model, new data can completely change all facets of marketing activity from strategic targeting and messaging to tactical campaign investment and roll out plans. As a result, it is crucial for companies to get to Stage Three as quickly as possible and remain ahead of competitors on the journey to Stage Four.