Personalizing B2B marketing strategies is a pain point in every industry. 83% of marketers struggle with effective content personalization due to their inability to forecast and adapt to the varying sales journeys controlled only by their customers. The difficulty increases when brands attempt to personalize their campaigns across multiple marketing channels with an expectation of real-time modifications. In the end, every email, social media post, case study, video, and infographic that makes up the marketing strategy fails miserably at engaging with consumers in a contextual and personalized manner.
Each customer receives the exact same messages in the same order. So, none of their underlying intentions are adequately addressed. The timing of delivery is not in sync with their curiosities. At the time that they seek information, empowerment, and education, they receive easily forgettable, bland, and generic content that misses the mark repeatedly.
As a result, marketers have watched as their rates of traffic, click-throughs, leads, and conversions derived from these near-meaningless marketing materials dwindle. Until they figure out how to access, integrate and leverage the right type of customer insights, B2B brands will be forever separated into two categories:
- those that customers gravitate towards, like Amazon
- those with a lackluster strategy that repels would-be customers, like Kmart or Toys-R-Us
Achieving Data Maturity
Data maturity is the optimization of strategically managed, defined, and fully developed consumer information that is derived from multiple external and internal sources. This data can be transformed into actionable insights used to construct proactive responses that align with the company’s marketing objective.
Research shows that only a mere 10% of companies consider themselves successful at disseminating data silos in order to aggregate consumer data. The remaining 90% of B2B brands have yet to achieve the level of data maturity needed in order to produce solutions that are conveyed with the right message- at the right time. Their marketing strategies lack the synchronization of intelligent data needed to design an engaging and meaningful customer experience.
As prospects progress through the sales cycle, their interests, needs, and actions alter- somewhat unpredictably. Without data maturity, the timing of content delivery remains independent from the actual thoughts, intentions, and actions of the viewer. What they see- and when they see it- is dictated by a predetermined strategy when it should be directed by refined insights into their interests and needs.
Achieving data maturity requires that brands begin targeting the type of useful consumer data that allows them to predict the behavioral tendencies of their customers. Unfortunately, buyer personas are not enough to achieve this standard of consumer familiarity. With buyer personas, marketers uncover segmented groups of consumer personalities. With mature data, marketers discover how their individual customers think and what triggers their actions.
Types Of Consumer Data To Aggregate
There are particularly insightful types of data that exponentially increase the relevancy and personalization of marketing content when incorporated. They improve the marketers’ ability to deliver targeted and personalized messages. When coupled with empowering artificial intelligence, they can also sync the timing of message delivery with the real-time intentions of their customers.
Website Behavioral Data
Website visitors leave footprints throughout the site as they navigate from one page to another. This data reveals the distinguished components that resonate with their audience while identifying the content that performs poorly.
Aggregating the total number of page visits, clicks, and login dates provide the behavioral data needed to improve the online presence of a brand. Questions that expose the most useful behavioral information include:
- How much time do viewers spend on each page?
- What type of mouse movement occurs on each page?
- What parts are scrolled over?
- Where do viewers spend time hovering?
- How much inactivity does the website receive?
- What areas of the website are irresistible to viewers and why?
Use the answers to create navigational routes. Follow the flow of traffic from one page to another, using the content to interpret the motivations behind the most prominent exploration paths. Determine what provokes viewers to take certain actions. Strive to understand the order in which they prefer to consume information and why. By identifying the behavioral influences that dictate viewer movement, brands can improve their content placement action plan. This data also illustrates the type of experiences viewers receive and the level of engagement that they offer, which will enhance the alignment of targeted messages with the individual intentions, interests, and affinities of various buyer personas. With this newly-achieved level of understanding, marketers can produce more personally relevant information more effectively.
Page View Behavioral Data
Once data is derived from the performance of the overall website, page visit behavior data will enhance the consumer profiles, so they incorporate the gravitational interests that dictate the level of consumer engagement. Questions that expose the resonance of each web page include:
- What exact pages did each visitor view?
- How many times did they view those pages?
- Did they view those pages regularly over the course of time?
- Did they read a review of the product before coming to these pages?
- Did you arrive at these pages after clicking on a link posted on the company’s social media page?
Much like Amazon recommends other products and customer purchases to personalize page experiences, marketers must collect page view behavioral data before they can implement a plan to increase customer engagement and loyalty. Marketers must first pinpoint the contextual messages that keep visitors coming back while assessing the elements that elongate the buyers’ journey.
Suppose brands notice that customers tend to visit a page 10 or 15 times before making a purchase. In that case, the task is to identify the absent or incomplete information that interferes with the relevance of the page. If customers are making purchases almost immediately, assemble the entire journey from start to finish to distinguish the behavioral patterns that result in closed sales. The more that is understood about the journey of individual viewers from and to each page, the more marketers will be able to improve the efficiency of implemented personalization techniques.
Influential Behavioral Data
Understanding page and site usage behavior allows marketers to understand the actions taken by viewers, but analyzing the intentions that lead to those behaviors empowers marketers to predict their actions. If marketers improve the ability to anticipate the pace at which visitors transition through different buyer phases. Then, they gain more control over the timing of the content presentation. That way, valuable solutions are available specifically when customers need them most.
The types of questions that expose the intentions behind consumer actions:
- What motivates a person to initiate contact with the company?
- What originates their interest in the product, and what sustains it?
- What causes them to stay longer on one page than another?
- What influences them to choose the next page to navigate to after they consume a certain message?
- What influences affect the probability of a first-time customer converting into a loyal one?
- What did customers buy after completing a previous transaction, and what motivated both of those engagements?
Identifying the influential behavioral factors behind the answers to these questions reveals predictive behavioral patterns. Use these revealed consumer reactions to create messages that meet their needs and expectations so they progress through each buyer stage quicker. By aligning the content with consumer interests and synchronizing the delivery to match their intentions, not only will marketers improve the effectiveness of their personalization tactics, but it will translate into more leads that convert into sales with less effort.
Final Thoughts on Personalizing B2B Marketing
Behavioral data is more than valuable engagement data used to increase the effectiveness of personalized content. It also maximizes the relevancy of marketing messages by improving the placement and timing of their presentation. Instead of using a blanket approach to improve audience conversions, use aggregated behavioral data to predict and control their sales-cycle experience.
Editor’s note: This post is by nDash community member Tiffany Winston. Tiffany writes various business articles and website copy on topics such as entrepreneurship, B2B marketing branded content, and more. To learn more about Tiffany or to have her write for your brand, sign up for nDash today!