Artificial Intelligence (AI) is becoming increasingly popular in the B2B content marketing space today. We have seen Predictive Analytics, Predictive Lead Generation, and now, Predictive Content being largely integrated into content marketing processes across the industry.
From healthcare to consumer brands to media & entertainment, marketers are now trying to leverage the power of machine learning to analyze data in ways they’ve never done before.
Indeed, predictive content is the new frontier of marketing personalization, and it’s gradually gaining currency among B2B marketing.
In a conventional marketing setting, it’s a common practice among content marketers to pass on leads to the sales team without knowing the lead status.
While content marketing automation tools have made it easier for marketers to measure the ROI of their strategy efforts, they’re still unable to gauge the lead nurturing status.
The inability to track content usage results impedes their ability to personalize communications, boost content efficiency, and marketing campaigns in general.
This is where predictive content scoring helps content marketers and sales reps alike.
One of the major challenges in content marketing is making sure all teams, including marketing and sales, can track the content usage and engagement status in real-time.
Predictive content seamlessly integrates content usage metrics with your CRM system, making it easy for both marketing and sales teams to track it and make informed decisions on how to follow up and close leads effectively.
Predictive content is designed to capture conversion-critical metrics from successful campaigns from the past and compares them vis-a-vis the behavioral data of various lead segments to reveal patterns.
This helps both the marketing and sales team to personalize their content based on the lead status and follow up accordingly. For example, you get content usage metrics from successful deals closed in the past; you can personalize your messages to improve your success rate.
What makes predictive content truly unique is that it offers content usage metrics which are deal-specific (industry, role, stage in buying cycle). This makes it even easier for both marketing and sales to personalize their communication messages to boost their success rate.
Lack of marketing visibility can result in wastage of valuable resources in your content marketing efforts. When you’re unable (or unwilling) to measure the efficiency of your campaigns periodically, you end up creating content that’s unlikely to nurture your leads or contribute to your sales pipeline.
As a matter of fact, this is what plagues many failed content marketing campaigns over the years. However, businesses are waking up to the unprecedented benefits of content scoring and graduating to predictive content models nowadays.
Predictive content removes any speculative content creation approach, saving your marketing team from creating ineffective sales content.
Ask any salesperson, and he will tell you that two identical leads are not created.
Predictive analysis teaches you how to correlate the actions of your existing customers to understand how to improve future marketing investments. This is most evident when examining the information that a good data analyst can obtain from the demographic and behavioral data of customers, in particular as regards lead scoring.
Historically, lead scoring has always been a collaborative activity between sales and marketing in which sellers say to marketers: "these are the leads that we want to receive immediately. And then marketing creates a sort of "scorecard" that measures the potential value of an incoming lead and determines (hopefully with automation tools, although some teams may still manage it as a manual process) whether the lead is "ready for a sale" or needs to enter a nurturing campaign.
Lead scoring, with predictive analytics, is transformed from a list of criteria from sales or marketing to a real data-driven view of your target customer.
When combined with a good automation tool, the rules governed by predictive analysis can quickly obtain scores based on demographics, behavioral, and psychological data. These scores determine whether the leads are "hot" and can be contacted immediately by sales, or if they need more time in a nurturing campaign before moving further into the more advanced stages of the funnel.
For those leads that are still in the early stages of the buying process, defining an appropriate lead nurturing plan should be the next step.
Lead-nurturing does not have a single approach valid for everyone.
The best campaigns make leads ready for sales to create personalized nurturing paths. Demographics and behavioral data indicate the right level and type of content to help push leads to the next stages of the sales funnel. Predictive analysis is, of course, the mechanism that makes all this possible.
Even as the predictive content is designed to aid your content marketing team to create better content, it’s still important that you use it intelligently.
Here are some points worth keeping in mind while working with predictive content.
In predictive content, there’s no room for personal bias or guesswork. Don’t let your “instincts” rule over predictive data. Sometimes, you may feel a particular piece of content is more likely to nurture leads better and faster, but it may not actually true.
Predictive content captures the behavioral data, effectively reflecting how the buyer is moving along your lead generation funnel. Therefore, if you allow your instincts to take over instead of following objective measurements, it will affect your process negatively.
Predictive content, much like content marketing itself, takes a while to produce desired results. Let’s face it — predictive content is super intelligent, but it’s not a magic wand. Like with every content marketing model, you need to set realistic expectations from predictive content.
Predictive content reveals which content pieces are resonating with your buyers and which are not. This essentially means you need to review your content periodically to see whether any potential buyers are interacting with your content. If most of them are not engaging with any specific content piece, don’t hesitate to remove it altogether.
Predictive content enables content marketers to understand buyers, track their journey, and create a better content experience for higher lead conversion.
By recognizing your buyers’ needs and their pain points
, predictive content helps you offer personalized and targeted content resulting in a healthier marketing-sales relationship.
1050 Words
Feb 25, 2020
3 Pages
