In the fast pace of Silicon Valley, we’re often seeing start-ups and even mid-size businesses shooting from the hip in their efforts to gain awareness and leads within their target audience. Always, we ask them to stop and think about these questions:
- Can they define their target audience?
- What do they know about them?
- How capable are they in their ability to reach them on or offline?
- What are the results they’ve gained? Not just in clicks, but in converted sales.
- What’s the ROI by program?
More often than not, the marketers we’re speaking to answer these questions as best they can, but with little confidence.
Insights Should Drive Your Marketing
We’re all for testing various channels, especially those that carry a relatively low financial risk, such as Adwords and Facebook ads. But we’d be remiss as marketing consultants if we didn’t push our clients to do the following:
- Analyze first to inform your approach.
- Establish KPIs and set up the reporting mechanisms that provide the associated results.
- Test and prove before you spend too much.
Think about targeted marketing in terms of Newton’s law: for every action there is an equal and opposite reaction. If you allow insights to drive your marketing, you’ll achieve more relevant and timely messages to your target customers, which in turn yields a higher ROI.
For today, we’ll focus on explaining the most common analysis approaches, each which yield insights that will define your target as well as inform your channels, positioning, creative and offers.
The first step and the biggest effort in order to perform any marketing analysis, is to gather, match, merge and clean a customer database. Today, it’s a faster process than ever before, thanks to a better appreciation for the value of CRM, inexpensive (often Cloud) CRM systems that already contain the bulk of customer data, such as Salesforce, and off the shelf tools to match and analyze data, such as Tableau.
Depending on the number of data sources and cleanliness of the data, this process can take anywhere from one day to four months. Once done however, any number of sophisticated analyses can be performed that will have a significantly positive impact in improving the ROI of a targeted marketing program.
Key components in preparing data for marketing analysis include:
- Contact details – cleaning, normalizing and updating
- RFM (Recency, Frequency, Monetary) data/Sales data
- Third party data append (to add demographic, behavioral and psychographic attributes, most commonly gained from Acxiom or Experian)
1. Profile Analysis
It’s one of the easiest and fastest to complete, and doesn’t require statistician skills to do it. Essentially, profile analysis provides various insights on your customers in terms of their purchase behavior, demographics and psychographics. A myriad of findings will turn up, from book readership to device usage to occupation – all better informing the marketer about who their target customer is, through what channels to reach them, and what kinds of creative and offers may be successful.
2. Segmentation Analysis
If a marketer already knows how to group the leads or customers they want to reach, a segmentation analysis will essentially divvy up the Lead or Customer database into those groups and provide insights to describe them in terms of past purchase behavior, demos, etc.
3. Cluster Analysis
This approach requires a statistician. Simplified, the analysis will reveal the groups in one’s database that are similar to each other, drawing borders between customers who behave or look differently. Again, each cluster can then be described to inform the marketing approach to reach them.
Another of the more sophisticated analyses requiring a statistician, modeling has the best likelihood for payoff for businesses with a large database or a high-cost product. Modeling finds lookalikes to a group of leads or customers already known.
For example, a marketer may have a known set of “best” customers based on their lifetime value. A model will find other leads or customers who look just like your best customers – giving a score or ranking to the entire database. The higher the score, the more they look like your “best.” The marketer then has the opportunity to invest their marketing dollars to whatever database depth is deemed worthwhile (usually ranging from the top 1% to 30%, depending on the model effectiveness and marketing budget available) and weeding out the rest.
Models can be based on whatever the goal – whether that is an attrition or loyalty focus.
Don’t be wary of investing the time and money to analyze. A good consultant or agency will listen to your goals, understand the data you have at hand and make an approach recommendation to attain a better return on your marketing investments.