B2B marketing refers to the marketing of products or services from one business to other businesses and organizations. Broadly speaking B2B marketing strategies largely depend on how brilliantly you have created a dossier for your ideal buyer persona. It includes many tasks like demographic research, listening to industry experts, analyzing existing customers, digital touchpoints to gather more data, and finally compiling and filtering a set of attributes that can be used to prospecting customers.

All these are not easy to execute tasks and there is a chance of delay in decision making which may impact revenue/ customer growth in this fast-moving world. Based on my experience and understanding of marketing, any seasoned marketer should use all existing marketing mix practices powered by AI and machine learning.

Let’s consider a few tasks of B2B marketer to discuss it further.

Improvement in Quality & Quantity of Leads

Potential of handling high quantum of data getting captured through various sources like Social media, company website or any other touchpoints and using intelligence it can provide quality chunks of leads where conversion rate to actual sales will be much higher at optimized cost as the focus will get shifted on identified target with high quality.

Considering scenario 1, we are targeting 1000 leads for Sales with an average 4% conversion and an acquisition budget is Rs 5 lac.

Considering scenario 2, we are targeting 400 leads for Sales with an average 10% conversion and an acquisition budget is Rs 2 lac.

Don’t you think if you create scenario 2 for your company, CMO (Marketing Head) will appreciate like anything?

This process is just a way to filter a set of data from your earlier targeted base with a very high probability to convert based on descriptive statistics, feature selection, principal component analysis, and some complex algorithm of machine learning which will help in developing artificial intelligence in the system to identify the filtered target base.

Campaigns Optimization

Intelligent targeting is the key to success for any campaign's effectiveness. We should think of very creative, customized, and meaningful content for our campaign to create demand for your product. Predictive analytics help a seasoned marketer to determine future customer responses or purchases based on past behavior and modeling patterns. You can anticipate the interest or desire to purchase and accordingly match it with your content for the campaign through the right channel at right time during the buyers’ journey.

Predictive analytics in the digital age is not an easy task but very useful once done. As said above, there are unlimited data streaming from various sources in different format i.e structured & most of the times unstructured formats like data fetched from Twitter/Facebook or any other digital sources. To capture those data and getting insight out of data with different variety and high volume requires skills of machine learning, big data tools, the concept of statistics, geometry, algebra & sometimes calculus also.

Hence, many companies prefer outsourcing as a better option instead of recruiting their own house talent. But in my view, they are wrong. Skills of data-based decision making combined with business domain knowledge can do wonder. Trust, all these practices are very much feasible, and many companies are using it. As it happens for any new process implementation, the first mover gets benefited always in this competitive world. Remember we are living in the world of blogs, podcasts, influential social media, email, and many more digital tools that can be a good source of data and anticipate decision-making with the power of AI.