The Importance of Good Communications, Collaboration & Data

By Nick Price

Good marketing communications don’t need to be complicated. Instead they should be genuine and simple and understanding of the fact that there is a human being on the other end. Content marketing offers B2B companies the opportunity to connect with real people by giving a voice to your brand from the people who work for you.
This is a highly effective approach, since 63 percent of consumers rank a “person like yourself” higher in credibility than a company’s CEO, and your employee’s voice offers a real connection. Yet almost three out of four B2B marketers still don’t think their companies are effective at content marketing, according to the Content Marketing Institute. Roadblocks include poor collaboration between marketing and sales, poor company branding, as well as issues with recruiting the right employees.
B2B marketers can benefit from collaborating across teams and expanding their concept of content from marketing tools, to revenue building tools. This includes integrating with sales teams and empowering employees across the organization to contribute their voice to content. Your employees are your brand’s greatest advocates, and it is worth investing their time and training in content.
Account-based marketing (ABM) has proven an incredibly effective way to break down the barriers between sales and marketing. While historically marketing teams take a broader view of the market and sales teams rely on the account-based approach, ABM creates a symbiotic relationship between sales and marketing teams who can both benefit from this kind of targeting marketing and communication.
“To break down walls between sales and marketing, ABM is pretty close to a silver bullet in that it aligns programs’ dollars and focus behind the accounts that the sales teams care about,” says Dave Karel, head of B2B marketing at LinkedIn. “So there’s inherent buy-in.”
Data is central to ABM’s rise and new data-driven technologies supply insights about the behaviors of prospects at target accounts. The rise of new cloud services for machine learning from companies like Amazon, Google and Microsoft is changing the landscape for these kind of predictive analytics services. Once complex techniques reserved for large companies, these tools are now available to smaller firms. While this DIY technology is exciting for B2B marketers of any size, these self-service models can put companies at risk of not understanding data.
Without the support of data experts, companies may be wasting their efforts. The challenge is not necessarily using machine learning algorithms, but is instead in optimizing and analyzing the data sets for meaningful business insights that determine the types of models to build. Without knowledge of how to extract, filter and match records, companies may fall short in their efforts and fail with marketing automation. The goal should be to interpret the analytics and use these insights to improve targeting and increase the relevancy of all the content that is pushed out. This can be challenging no matter how accurate your predictions are. You will still need to figure out how to integrate predictive scores with the company’s technology stack and day-to-day workflows, which can be overwhelming. Business teams have to weigh the risks of taking a complete DIY approach over investing in the services of a vendor to get their system up and running. While self-service modeling might sound attractive, it may end up as less work if you work with a vendor.
In the end, it’s more important that your teams spend their efforts learning to work better together and developing the brand’s voice through great content.

Nick Price

Be the first to know

Subscribe to receive the latest B2B marketing research, whitepapers, articles, infographics, ML news, and more.