Insight, Analytics and the New Marketing
From Math to Insights
The last 2 chapters of the Math Marketing paper describe how you can make it work for you in order to increase accountability and to generate powerful insights. This article on Chief Marketer (http://chiefmarketer.com/marketing-roi/0616-marketing-accountability-tips/) described 8 steps to greater accountability. The last chapter discusses Math Marketing in the context of generating insights.
1. Build a single customer view
Owning your own data is never a bad idea. As described earlier, many companies have been building corporate data warehouses that create a single view of all their customer data since the early CRM days. This is often an expensive and labor-intensive task. But if done correctly, your database can be an incredibly valuable asset. Tesco in the U.K., for example, estimates that 16% of their margin is attributable to the knowledge they get from their customer database—that makes their database a $3.2 billion asset. One of the key challenges in the future will be the increasing amount of customer data now generated outside of corporate systems. That data is owned by platforms like Facebook, Twitter, Google, Microsoft andYahoo!, rather than the companies themselves. We expect these companies, or even third- party data clearinghouses, to develop solutions that will enable companies to integrate these data sets with their own data warehouses.
2. Mine your data
Your data is only as valuable as the insights you distill from it. This is what Math Marketing allows you to do. There is a whole range of techniques available, but we suggest you start with the basics and prioritize your data mining efforts based on the questions they will answer. Do you know who your best customers are? What drives your profitability? How can you find prospects with the same profile? What can your data tell you about how to communicate with customers and prospects? These questions will determine whether you need a value segmentation, an attitudinal segmentation, a lifetime value model, an anti-attrition model, a browsing typology or any other Math Marketing tool at our disposal today.
3. Learn from search-intent modeling
Search data is rich in information. And it’s free. Search intent modeling tools mine that data and provide insight based on the search terms that consumers use to find your brands/products. This can teach you a lot about the thought process of your target audience and the words they use to talk about your brand, which can improve the effectiveness of your overall communication tremendously.
4. Plant your listening posts
Social web platforms such as blogs, microblogs, forums, social networks, and opinion and review sites give you another relatively easily accessible source of consumer data. This data can be used to generate insights in a manner similar to search intent modeling. Listening post technology can collect data from these platforms and perform semantic analysis of the conversations that are happening there. This can give you more insight into how many people are talking about your brand, whether they have positive or negative opinions and which other brands or characteristics they associate with it.
5. Revitalize your primary research
If you want to know what consumers think, just ask them. This is how primary research works, and this is why it has been the main data source for generating insights for a long time. But today’s primary research is an entirely new discipline from what it was a decade ago. Social communities and online survey tools have dramatically cut the costs of primary research. These tools can be used for idea generation, polling and even in-depth interviews. And they can be deployed very quickly. They even give you the ability to leave the feedback channel with your customers open at all times, providing your marketing group with a constant influx of fresh insights.
6. Simplify for increased actionability
Simplicity leads to action. This is definitely true for insights. But keeping things simple in a Math Marketing world is not obvious. Math Marketers are specialized in analyzing the vast amounts of data in our digital world. They often need to be taught how to embrace both the complexity of that data and the simplicity of actionable insights. There are plenty of techniques and tools that can help Math Marketing insights become more actionable. These range from personas and customer portraits to rulebooks and guidelines. Simplicity is key with all of them.
7. Empower the end user
Most companies spend far too little time on this last point. They put all their effort into generating insights and occasionally formulating them into simple, easy-to-digest formats only for their work to end up collecting dust on the shelf of the head of marketing intelligence. You should develop insights with end users in mind. These can be customer service representatives, new product development engineers, creative and design teams, or anyone else who could end up benefiting from your insights. Involving them in the insight generation process can help focus your efforts and will almost certainly help increase the adoption and use of those insights. This can often be achieved through small organizational changes. Consistent communication of insights to end users can be an
easy but important first step.
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