Any article about business analytics had better start with a definition. Here is mine: business analytics is a methodology that encompasses the whole process of transforming data into valuable and actionable information. This covers gathering raw data, enriching and managing it, analyzing it via a knowledge discovery process, reporting new insights to users in meaningful and relevant ways, and then harnessing this deeper understanding to support decision-making. This is why analytics plays a crucial role in the evolution of marketing.
Marketing has been around for as long as civilization; I have no doubt that early traders were artful in promoting their wares, even before money was introduced. But marketing as we know it – using modern communications to reach mass markets, promoting brands and offers – only emerged about 150 years ago with the formation of companies and brands, as well as the expansion of cheaper and faster transportation.
Early customer marketing focused on lists: creating and storing details of customers and prospects. Lists were small, limited by the physical space required to store, collate and select record cards. Then, with the computer, came the database, making marketers’ lives more complicated. Even today, managing the database is a continuing challenge for marketers – gathering data and keeping it accurate. And that’s before regulatory demands for proper data governance and stewardship are factored in.
Lists remain the currency of direct, outbound marketing. But list-based marketing suffers from one fundamental problem – cost. Reaching out to thousands, perhaps millions of customers, with one generic offer is rarely justified given low response rates.
By the 1980s, database marketing employed data analysis to subset lists into collections of records (segments) that shared common features and could be processed as groups. Data mining – the statistical process of finding hidden patterns and trends in data – matched groups of records with predetermined criteria such as propensity to buy or prior behavior. Marketing to segments improved the ratio of offers to acceptances – even relatively small uplifts in response rates could dramatically improve the net margin of a campaign. Better yet, data mining techniques could ‘learn’, building results from previous campaigns into the models to improve targeting accuracy in the future. Analytics has been the staple of database marketing ever since. It’s still outbound marketing, albeit more efficient and effective.
Smart selling to smart buying
Recent years, however, have witnessed a completely new phenomenon made possible by widespread access to the internet. The ‘market’ is doing its own analysis, comparing offers, sharing experiences with products and services – in essence taking control of brands. Marketing has had to adapt to the shift from ‘smart selling’ to ‘smart buying’, as clients become increasingly savvy to the marketing techniques of the past.
Now, still working hard to distribute messages to the right audience, organizations also need to manage inbound communications, addressing queries, resolving complaints, gathering feedback and maintaining a consistent, high-quality user experience. The modern marketer who ignores such things risks being the target of a client revolt. In minutes, social media networks can turn one disgruntled client complaint into a boycott. Worse still, social networks resist attempts to manipulate public opinion; woe-betide the organization that gets caught trying to manipulate its own standing in social networks.
So today’s marketers need to manage outbound communications more tightly than ever, making sure exactly the right offer is made to the right client in the correct way; manage the interface between organization and client across all channels; maintain a consistent experience; and analyze social media chatter to address concerns before they escalate into damaging backlash. And if that weren’t hard enough, the global economic downturn has left marketers doing it all with frozen or reduced budgets.
So the time is right for business analytics. More than ever, marketers must base decisions on reliable data that is both comprehensive and comprehensible. Using proprietary data – about customers, suppliers and internal processes – as a competitive differentiator, business analytics lets marketers identify activities that provide the greatest value. They can optimize ongoing activities and find areas where savings exist. They can transform how the organization acts – using social media to engage in dialogues with, rather than broadcasting to, customers. They can even use techniques such as sentiment analysis and social media analysis to understand those who did not buy the product and track what people are saying about their brand. Perhaps most importantly, they can transform the business – using new insights to identify new service offerings for existing markets, forecast more accurately and so control costs better.
There is always more value to be gleaned from proprietary data – data about spending habits, preferences, unaddressed needs. An organization’s data and the knowledge it holds provides a unique competitive weapon. Products can be copied; but know-how is much harder to imitate. Imagine an organization that can use a deep understanding of its customers in one service line to provide the intellectual head start for an entirely new product or service. Now look around you: it’s already happening.
Learn how to put analytics to work for you. Download A marketer’s guide to analytics