Demand Intelligence: Empower Your Strategies With Actionable Data via @sejournal, @alexanderkesler

In the context of B2B marketing, demand intelligence is a consolidation of data from various sources filtered through an actionable lens to provide critical insights.

This data can be utilized to anticipate client demand and implement targeted strategies to engage key stakeholders.

Simply put, demand intelligence enables marketing and sales teams to identify who is interested, why they are interested, and their likelihood to convert. Obtaining this data, however, can be challenging.

In this article, I will share best practices for sourcing, analyzing, and applying demand intelligence to maximize your return on investment (ROI).

The Importance Of Collecting Actionable Data And Leveraging It Effectively

The cost of missed opportunities due to outdated or incomplete data can quickly reach millions. Consider the time and resources invested in campaigns that target obsolete leads or contacts with limited information.

With prospect data averaging a lifespan of just nine months – often due to frequent job and title changes – relying on old data is a waste of both time and effort.

Only 16% of the marketers interviewed for our own 2024 market research utilize advanced buyer and account intelligence to inform their sales and marketing strategies.

This reveals a significant opportunity to leverage data to pinpoint the right accounts and personas – those who are truly qualified for your solutions – for more effective outreach.

To drive demand performance, sales and marketing teams need up-to-date, actionable data that accurately reflects the buyer’s behavior and preferences in their purchase journey.

Without this insight, nurture campaigns will fail to hit the mark, leaving prospects to disappear from your sales funnel entirely and, often, cause them to switch to a competitor.

What Is Actionable Data?

Consider actionable data as real-time insights that reveal prospect intent, behavior, and preferences, while also supporting predictive analytics.

This type of data provides valuable takeaways about prospects, helping you identify their pain points and tailor your outreach effectively.

With accurate and timely information, you can craft messaging that resonates with current prospect challenges and drive engagement for your solutions.

Sources of demand intelligence include:

Technographic data: Identifying prospect technologies to uncover opportunities for increasing your tech wallet share. Engagement data: Insights from website interactions, blog activity, social media, and email communications. Buyer personas and key account profiles: Detailed profiles of existing target audiences, decision-makers, and key accounts. Buyer intent data: Behavioral cues, such as frequent searches or downloads related to specific solutions, indicating a readiness to purchase or, at least, buyer interest in your solutions. Analysis of successful conversions: Examining the behaviors and patterns of successful conversions to inform future demand intelligence. Average deal size and revenue: The average deal size can act as a benchmark for future sales opportunities. Client lifetime value (CLTV): Client success teams can identify the common characteristics of prospects that generate the highest long-term revenue.

The key is to unify these diverse data sources into an intelligent demand system – one that reveals where engagement is happening in the funnel and via which channel, in order to predict where it is likely to occur in the future.

This approach holds immense potential for organizations to fuel precise and timely engagement strategies that drive meaningful results – because they can engage the appropriate buyers with the most relevant messaging at the optimal time.

How To Collect Demand Intelligence Data

Building your proprietary database enables you to track market behaviors and trends, and develop strategies to address them effectively.

The best sources of information for your database include:

First-party data: Information collected directly from your channels, including your website, social media, events, and customer relationship management (CRM) analytics. Data partners: Verified data partners can provide access to valuable first-party intent, behavioral, and technographic data. Client-facing teams: Insights from your sales, marketing, and client success teams offer valuable first-hand perspectives on existing clients. Community engagement: Utilize social listening and sentiment analysis tools to understand what clients say online and gather insights from reviews. Surveys and feedback: Directly ask clients about their needs and pain points to inform your outreach and refine your solutions.

Enhance these insights by analyzing industry benchmarks and competitor reports that align with your target audience. If your budget permits, consider investing in the expertise of external specialists.

Combining these resources will help you develop a comprehensive demand intelligence profile.

How To Build A Framework For Collecting, Analyzing, And Applying Demand Intelligence

Below is a three-step framework to develop your demand intelligence strategy:

1. Build A Database Primed For Demand Intelligence

Your first step in leveraging demand intelligence as a growth driver is to gather insights from across your organization and create a secure, centralized dataset in a tool like your CRM or data warehouse.

The goal is to establish a unified view of your prospect and account data that can be easily accessed by your client-facing teams.

Focus on essential campaign-driving information like pain points and intent data, which can be tested to refine your demand intelligence.

Intent signals can be a valuable addition because they help marketers understand prospect behavior to enable the tailoring of services more precisely to buyer needs.

Before testing your dataset, you will need to perform some housekeeping:

Leverage automated data cleansing software or AI to identify duplicates and errors. Set up filters and criteria to highlight actionable factors, such as budget range and buying group size. Enrich your data with synthetic, or stand-in data, where necessary. Ensure your data practices comply with regional privacy laws like GDPR and CCPA.

2. Launch, Analyze, And Adjust

Launch a short-term campaign to test your first dataset and validate your existing demand intelligence sources, filters, and criteria. For example, this can be in the form of an awareness campaign via email and social media.

You will need to set up processes to ensure data flows into your analytics, not only to measure the results but to enable continuous assessment and improve the quality of your demand intelligence.

This can be done by:

Gating content with forms. Creating UTM tracking links. Using heatmaps to measure website engagement. Sending email touches through your CRM.

Once your test campaign is complete, analyze the results to refine your data further. It is also worth adopting processes to gain feedback directly from your audience, such as through surveys or sales team outreach.

Focus on KPIs and metrics that will help the organization achieve its GTM and growth goals, such as:

Conversion rate. Engagement metrics such as downloads, click-through rates, web traffic, bounce rate, and social engagement. Buying group engagement on an account level. Opportunities generated. Sales or demo bookings. Satisfaction scores (NPS, CSAT).

3. Continuous Optimization

Once you have your campaign results, translate them into actionable insights to inform ongoing marketing and sales strategies.

Processes that can be adopted for this purpose include:

Keyword and topic analysis: Identify the themes and discussions that generate the most interest among your prospects. Engagement timing and frequency: Track engagement to understand interaction patterns and plan strategies accordingly. Buyer’s journey assessment: Analyze the buyer’s journey and evaluate how prospect behavior aligns with it. Consider potential areas for improvement. Effective content touchpoints: Identify which touchpoints are most effective in driving discussions among decision-makers in buying groups.

Adjust your strategy with targeted changes to your messaging and UVP, tracking the impact to refine further. It is better to make select, strategic changes that can then be monitored to assess performance.

Three areas of improvement to prioritize are:

Maintaining an updated database: Regularly assess the quality of your data and its relevance to your organizational goals to ensure it remains current and useful. Refining buyer intelligence collection: Continuously improve your data collection methods based on insights gained, feedback received, and any changes in your objectives or technology. Fostering organizational alignment: Share and align data across teams to promote collaboration and innovation within the organization.

Done well, demand campaigns have immense potential to amplify an organization’s bottom line. The goal of demand intelligence is to optimize strategies to better engage, nurture, and convert buyers – no matter where they are in their journey.

Businesses focusing on demand generation are better equipped to navigate the complexities of the evolving B2B landscape and drive sustained revenue growth.

Key Takeaways

Prioritize first-party data: Actionable data from owned channels and partners will help you to better understand and anticipate client demand. Gain feedback from client-facing teams: Unique and timely client insights can be sourced from your own teams to guide your demand strategies. Build a clean database: Focus on essential campaign-driving insights, such as client pain points, intent, and account information, while avoiding unactionable data points to not bloat your database. Test, analyze, repeat: Continuously update your database to reflect evolving audience needs and the value of your demand intelligence.

More resources:

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