Marketers claim to know their customers because they have captured demographic and historical transaction information about them but would you have married your spouse based on age, height, address and the fact that they bought shoes once? I think not. Why should marketers think this enough to truly address the needs of today’s customers?
Many marketers are doing a very good job an incorporating traditional data critical to being able to target marketing efforts.
Data such as:
- Self-declared demographic information
- Marketing inquiries
- Sales leads
- Orders, payment history
This information is a great place to start. There is no doubt that applying advanced analytics help marketers find patterns and trends while also predicting what is likely to happen next.
Think about being on your first date with you spouse. The conversation starts with the basics:
- Where are you from?
- Where do you live now?
- Where did you study?
But quickly moves to:
- What is your opinion of the President?
- What do you do for fun?
- What do you really dislike?
Now think about applying this in a business context. As a marketer, I would like nothing more than to put an offer in front of customers and prospects that would not only speak to their business need but would also speak to personal likes. How can you do this?
Every interaction is an opportunity to get to know your buyers better.
Traditional interaction data from a marketing automation system such as Unica, Eloqua, Marketo or Neolane is a valuable source of information about buyers’ behavior. By capturing all interactions, regardless of channel, allows marketing organizations to apply predictive models to predict which customers are likely to respond to marketing offers via which channel and how frequently. Using predictive models as part of a broader customer analytics initiative helps marketing organizations identify which buyers to target and personalize offers for cross and up-sell opportunities
Great, we now know which offers my buyers will likely respond to and how frequently! Now, go back to my first example – the date. Getting to know your buyers personal preferences allows you to gain a deeper understanding of customer attitudes, preferences and opinions to make them part of the decision making process. Think about collecting customer opinions, attitudes and interest via surveys or data collection. Use the interaction opportunity to capture a hobby or other personal activity. Then apply this in your marketing activities. If your buyer likes golf, find a way to incorporate it into your outreach (e.g. my marketing team has used direct mail/dimensional mailers giving away a free driver!).
Social Media is another data source which can provide tremendous insight into customer opinions, both positive and negative. Apply social media analytics to get the real opinion of your products to ultimately engage brand advocates and detractors in a conversation. Social media analytics allows organizations to capture consumer data from social media to understand attitudes, opinions and trends.
They key here is not to look at each of the pieces of data as stand alone pieces of information. It is about combining them to get a “thumb print” which identifies the uniqueness of an individual.
Please feel free to connect with me on Twitter to discuss further @BrendanRGrady