Personalizing The B2B Relationship - Part 1: Leveraging Your Big Data Analytics

Many business-to-business (B2B) companies have understood the need, and have adopted, cutting-edge strategies used by their business-to-consumer (B2C) counterparts. For those B2B marketers who remain on the fence, this series addresses why, and specifically what to incorporate.

The world of B2B Marketing is witnessing profound changes attributed to:

·      Evolving Customer Expectations

·      Technology Trends

·      Increasing Influence of Digital Marketing

·      Changing Customer Purchasing Dynamics

Below we focus on one of the cutting-edge topics in B2B Marketing – incorporating Predictive Analytics. We address the creation of a relevant, contextual, and personalized interaction with your B2B customers over an extended period of time, covering the entire sales lifecycle.

As B2B marketers, the need to continuously adapt to the changing environments with new disruptive tactics is vital to the growth and sustainability of your business. To ignore this reality means to run the risk of encountering greater disruption -- by the competition. So, where do you begin?

Consider global B2C leaders such as Amazon who have taken Personalization, Customer Engagement, Customer Experience (CX), and Customer Relationship Management (CRM) to another level. They've deployed big data and analytics tools, developing in-depth understanding about unique needs and preferences of customers, driving customer loyalty and satisfaction to the highest possible levels.

Forrester Research posits that 2017 is the year B2B marketers are organizing themselves around the customer life cycle, significantly augmenting customer intimacy and insight skills. Skeptics can argue that since the level of personalization required in B2C marketing is much higher than B2B marketing, big data and analytics is not useful for creating personalized marketing for B2B customers. But this simply isn't true.

B2B buyers value a personalized approach. In fact, given that the lifetime customer value of a B2B customer is much higher than a B2C customer, the importance of big data analytics to create customized marketing tactics is extremely important for B2B marketers.

Just like in the B2C space, analytics can provide deeper insights into the purchasing behavior of B2B customers, allowing you to make proactive marketing strategies to augment sales. Unlike their B2C counterparts, however, B2B buyers need personalized or customized information, since they often lack homogeneity. Marketing tools offered by companies such as SAP can help access real time data to offer customized solutions and information to their target customers. 

With multiple stakeholders and decision makers in an organization, marketers can provide contextual information to make a successful sale. Hence, the definition of personalization in B2B marketing can take the form of relevant and appropriate information, content or solution, that best addresses customer needs.

The concept of B2B personalization extends beyond personalized emails or purchase suggestions and penetrates deeply into the later stages of the sales cycle. You can effectively utilize big data and analytical tools to nurture long-term relationships with your customers.

Personalization, continuous engagement and interaction, and the utilization of technology tools and big data analytics shapes and refines your B2B Marketing strategies and tactics. Helping your customers acquire and serve their customers more effectively is another perk -- with more personalized products, services or support. This can be done by adopting two strategies: one for your B2B customer, the other for your customer’s customer.

Coming soon in Part 2, our focus will shift to tips, tactics, and insights to regularly interacting and engaging with your B2B customers.

(This was originally published in the Southern California Business Marketing Association Blog)