By Rob Daleman

For today’s business-to-business (B2B) marketer, proper market segmentation is a key step that will make or break your marketing campaigns and go-to-market models. While not as focused as account-based marketing, a well-defined segmentation model offers the ability to break down a larger market to better target your most powerful value propositions and messaging to the right customers.

The great thing about being a B2B marketer in Canada is that the market isn’t too large for the average marketer to analyze and create a defined segmentation model that is both accurate and actionable. It is an exercise worth pursuing: the increased focus is exceptionally helpful in driving increased response rates and lower digital advertising costs.

There is no “one size fits all”
I have had the privilege of working on several market segmentation models for a major computer manufacturer, a leading telephony provider and several small technology companies. While every company requires a unique model, the base approach is always similar: a comprehensive review of the current install base and potential market broken down by company size, industry and geographic distribution. Comparing the sales versus potential market in this way is often very revealing, highlighting areas of over- and under-performance. Strong sales in a particular vertical is often indicative of a strong use case for your product or service that might be leveraged with other prospects. But inconsistent sales across geographic zones may indicate an opportunity for additional advertising and sales coverage. Leveraging these insights is an important first step in defining your go-to-market strategy.

Don’t ignore outliers
The first lesson I learned in segmentation is not to ignore the outliers in your customer data! I remember one account that was labelled as a small business but which had been purchasing large scale enterprise server and storage solutions far beyond what their firmographic data would imply. When we dug down deeper to better understand the account, we found out this company had advanced requirements because they were doing video rendering for blockbuster movies. Clearly, their needs were very different than those of the average small business: and our model needed to be adjusted accordingly. Looking for these outliers will help you fix your model to include niche customers that would benefit most from your products and solutions.

Bad data = bad models
Every customer database I have ever worked with has had challenges, including duplicate and outdated company information, non-standardized and duplicate transaction information and a lack of proper contact data.

The first step in developing a solid segmentation model is to ensure that data is properly cleansed and de-duplicated to create a data set that is both complete and accurate. Data cleansing should be executed on two different data sets: a market dataset that is representative of the entire Canadian landscape, and a transactional dataset that includes your current customers and their purchase histories. With these two core datasets cleansed, the initial analysis may be completed.

Moving forward with data integration
Up to this point, we have developed a segmentation model based on who customers are, such as by size and vertical. The traditional approach may stop here, but marketing technology allows us to do much more today! Is your business ready to focus instead on segmenting customers based on their actions?

Using data derived from marketing automation tools, advocacy platforms, digital experience platforms and CRM systems, it is possible to create 360-degree views of your customers. This data can then be used to analyze the level of engagement of your customers by account, vertical, size or geography to determine who your most active customers are and projecting this information onto the wider market to better inform your segmentation model.

Often, this type of analysis offers insight into important shifts in the marketplace, such as companies from a new vertical beginning to engage with your organization more often, potentially revealing that your solution is finding a home in new markets or with new customers.

Leveraging this information is powerful because it allows us to move beyond using historical records, such as transaction histories and other data that is rooted in the past. It permits us to see how different accounts are interacting with us today, through online tools, and to build segmentation models based on anticipated actions. For example, we use this type of data to understand how, in aggregate, different verticals are engaging with our content over time and how they are traversing our product line. This informs our content planning team to ensure we are delivering the right information at the right time for both current and potential customers.

Make your data even richer
Today’s marketplace is awash in high-quality third-party data sources including firmographics, mobile data, anonymous cookie data, demographics, psychographics and online sentiment analysis. Marketers need to proactively plan for the future, as the number of data sources available is set to increase exponentially as more connected devices come online. All of these data points should be considered as potential assets to help your organization further tune your segmentation model.

To leverage these emerging data sources, consider an on-demand data approach that allows your organization to be future-ready and offers the ability to cleanse and enrich your data sets as new attributes become available. Utilizing these modern forms of customer segmentation serves to make your brand more powerful than ever before.

Rob Daleman is vice president, corporate marketing for Quadient ( Quadient is a leading provider of customer communications management (CCM) technology, enabling organizations to create better experiences for their customers through timely, optimized, contextual, highly individualized and accurate communications for all channels.

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