Data-Driven Marketing for B2B Marketers A data-driven approach is giving both marketing and sales the same view of the client
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Over the last decade, brands have changed how they go about doing their business, thanks to data. Every aspect of the business has transformed due to the availability of accurate, measurable and consistent data through automated routes and collection tools. Marketing is no different. It is said that the marketer of the future will be a data scientist. While the creative and artistic aspects of marketing are still relevant, the strategy and the insights that fuel these softer aspects have become data-driven.
Taking the Relevant Data
B2C marketing has had a head start in adopting data due to reliable sources of collection and the readiness of its target audience in sharing information. The problem with B2B marketing has been accessing to relevant and credible data. However, B2B marketing is adopting fast with tools to map onto unrelated, non-constructed data and effectively infer meaningful insights.
One of the immediate impacts of this is the streamlining of marketing and sales processes. A data-driven approach is giving both marketing and sales the same view of the client; current as well as prospective. This is helping both the functions to bring synergies and pave the way to the most effective marketing method – Account Based Marketing (ABM). ABM is a predominant B2B marketing strategy where a brand considers an individual (key stakeholder) or an account or an industry vertical as a market of one and targets them with highly personalised content, resulting in better ROI.
The data-driven approach is also helping B2B marketers to deliver persona-based marketing where a customer persona is developed and then the highly personalised content is targeted at every stage of the buying journey. Earlier the prerogative of B2C, persona-based marketing is now helping B2B marketers to customize and personalize their communication experience.
Difference in Functioning
Unlike B2C, the B2B marketer must talk to various stakeholders within an organization to make a meaningful impact. The level of detail, the value proposition, and even the business impact of a purchase decision are perceived very differently at various levels within an organization. What a CXO looks for is very different from what a functional head possibly seeks. A data-driven approach is helping the B2B marketer to bridge this gap in a constructive and cost-effective way.
The biggest impact of data-driven approach is how the B2B marketer is viewing the data. Since external data is not readily available, internalizing a data-driven practice calls for a systemic shift; in the collection of data, prioritizing sources, analyzing methods and more importantly, how the derived insights are leveraged for implementation.
Primarily there are two types of data collected. Descriptive or firmographic data and behavioural or technographic data. Both the data buckets are defined by look-alike modelling, critical to B2B marketing to find patterns in data and leverage to communicate to the brand's audience. Only when a B2B marketer starts looking for these patterns, will s/he be able to leverage data to its best advantage.
Data and Mainstream
The data-driven approach also means empowering data to manifest itself. This means, on one end, to increase the reliability of input data through closer mapping data collection across all customer touch points – from pre-sales to support. On the other hand, deploying ML, AI and predictive modelling to ensure data is analyzed and patterns identified.
There are several client touch-points where a B2B marketer can source data, analyse and implement inputs into action. For instance, events, whether virtual or on-ground experiential ones, can be an excellent source to quality and reliable information. Similarly, other touch points such as social media, points of sale, website, ratings and reviews, word of mouth, etc. constitute a perfect ground to source and test insights derived from the analyzed data.
A data-driven B2B marketer should, therefore, aim to build a data-centric marketing ecosystem and not focus on data in silos. This will help in true customer connect and create a meaningful brand experience.
