Segmentation and the art of data science

The difference between demand generation and account based marketing (ABM) is sometimes likened to fishing with a line versus hunting with a harpoon. For B2B brands selling big ticket items, ABM can seem a very attractive proposition and it is gaining traction.

So how can you make this approach work for your brand? Clearly, the quality and reliability of data is a critical factor. There’s no point investing in ABM if you can’t connect with the right people in target accounts. However, the role of data is much broader than that. It can also facilitate identification of hot prospects within entirely new industry sectors.

Data driven segmentation and targeting

Traditional B2B segmentation – focusing on features such as company size, industry and geographic region – only provides a narrow view of potential prospects. Modern data science draws on richer, more detailed business information. This needs to be actively embraced in ABM since it can reveal a strong alignment with segments and verticals that you may have never targeted before. Robust analytics can provide the evidence needed to justify the exploration of new opportunities beyond the well-trodden path.

One way to choose your customers, rather than having them choose you, is through the identification of lookalike audiences. List your best customers, and determine any common attributes. In addition to traditional segmentation features, it can be useful to consider wider factors that are relevant to your offering. If you specialise in tech products or services, analysing clients’ internal technology environments might provide valuable indicators: What is their level of tech maturity? What technologies have they invested in over the past 12 months?

Ultimately you need to find the best set of data that gives you the insights required to target and serve current and future customers intelligently. Be prepared to learn about industries you’ve never targeted before, ensure you understand their pain points and deploy resources to instigate open dialogue about how their issues can be resolved.

Looking ahead

Data science is constantly evolving, and the amount and type of data we can access today is much richer and more informative than the simple firmographics of the past.

This brings advantages to B2B brands at many levels. As well as shining a light into new sectors that are ripe for targeting with ABM, it can enable the development of granular personas for individualised marketing messages and content.

When it’s done well, ABM facilitates more strategic budget allocation. Once you have earmarked accounts to target, marketing can be tailored to reach the right people at the right time with the right messages. A larger percentage of sales and marketing efforts can be geared towards those with the best fit, and a smaller percentage to a wider audience.

Best in class sales and marketing teams of the future will demonstrate a fleetness of foot in their adaptation and execution of activity based on newfound evidence. ABM is about long-term strategies, not ad hoc campaigns. However, companies that can achieve and maintain a meaningful dialogue with prospects are likely to condense the sales cycle and realise better, quicker returns. 

Some people heralded 2015 as ‘the year of ABM’ and industry pundits suggest that many B2B organisations will invest in technology to help drive ABM in 2016. If you fall into this camp, a combination of fundamental data hygiene and sophisticated data analysis will help maximise the investment.