The Data Advantage: How Predictive Analytics Powers Smarter Lead Gen

What if you could be the "master conductor" of your lead generation efforts, where you could step up to the podium and effortlessly wave the baton to orchestrate every signal to your best prospects and engage them in ways that lead directly to sales? As a business owner, you would surely want to be that conductor waving the baton, wouldn't you?

For faith-based businesses, you face unique challenges every day trying to connect with the right audience, while also staying true to your goals and values. That's why the idea of being a conductor with a baton is so enticing. Predictive analytics can be like that baton. It can help your business focus on leads that are most likely to convert to sales and reduce mass communications and endless cold calling lists.

"In our competitive world chock full of marketing strategies, predictive analytics can help you determine which clusters of prospects may be more reachable and through which channels and messages," says Name at Company. "This predictive technology will not only increase conversions but also make resources more efficient!"

According to a study by Harvard Business Review, companies that adopt predictive analytics are seeing substantial gains, including:

• 51% lead in to deal conversion rates
• 10-15% increase in conversion rates
• 15-20% increase in deal size

What are predictive analytics in lead generation?

‍Predictive analytics in lead generation is a business strategy that combines historical data, statistical algorithms, and AI machine learning techniques to forecast future customer behaviors and trends that lead to positive outcomes (such as increasing revenue).When it comes to lead generation, it uses past and current data about your prospects/customers to predict which leads are more likely to engage and convert to sales.

Predictive scoring: The "heart and soul" of predictive analytics

Predictive scoring is the analytical process that assigns a value, or "score," to each lead based on the likelihood that the lead will become a customer. It scores various data points you've collected, such as:

• Previous engagement with your website, social media, or content
• Demographic details, such as job title and location
• Behavioral patterns, such as email opens, clicks, downloads, and event attendance

Essentially, predictive scoring tells you WHO the right leads are to focus on. For example, if your data shows that leads who download content from your website and also visit your social media app exhibit a higher percentage of buying behavior, the predictive model will boost the scores for those leads that exhibit the same behaviors. The benefit of this predictive scoring is that it can score updates in real time, so you always have the most recent opportunities.

Intent data: The "beat/tempo" of predictive analytics

While predictive scoring is the heart and soul, intent data is often referred to as the beat of predictive analytics. It tracks your prospect's behavior, content they read, keywords they search, pages they click and so on, and offers insights into your prospect's interests and behaviors. By doing so, it helps determine WHEN and WHY a lead might be ready to convert. Types of intent data include:

• First party is the data collected from your own website visits, content downloads, and email engagement
• Zero-party data occurs when customers willingly share their preferences, purchase intentions, and other personal information through surveys, forms, and other means
• Third-party data is collected from external sources, including partner websites, social media platforms, and other relevant resources

Predictive scoring of intent data enhances lead generation by:

• Focusing on high-value leads where the highest scores are the leads your team can reach out to
• Personalizing messaging based on the lead scores and delivering content of interest to the prospect
• Improving conversion rates by targeting active prospects and leads at the right time
• Optimizing resources and reducing efforts on low-scoring leads

Integration and Implementation: Putting your data into action

Collecting and scoring data is important but putting it all into action is another matter. That's where predictive analytics integrates the predictive scoring and intent data with broader, robust analytics through CRM/AI platforms to provide an extensive view of quality leads. This data dashboard or predictive modeling can help identify the HOW--which channels and messaging are most likely to convert by:

• Segmenting leads by score and other attributes to tailor marketing and communications strategies
• Automate lead routing by assigning high-priority leads to the most skilled sales teams
• Monitor leads and conversion trends through the sales funnel to adjust tactics
• Measure campaign effectiveness by analyzing which channels, messages, and touchpoints drive the best results

The key to making this integration work is ensuring that all your teams—your sales, marketing, IT teams, etc.—are on the same page, collaborating, and properly "tuned up" for the concert. They need to work closely to exchange insights and data, ensuring that all data from all touchpoints is unified. This action also allows continuous refinement of predictive modeling and scoring. By measuring how well lead scores on the intent data align with actual sales, businesses can adjust their algorithms, incorporate new data sources, and refine AI learning to improve accuracy over time.

ALERT: Beware of data quality issues

While predictive analytics offers powerful advantages, it's not 100% foolproof. It relies heavily on all the underlying data. Bad data can lead to inaccurate scores, misdirected outreach, and wasted resources.

Here are some of the top data quality challenges you need to be aware of:

• Data decay occurs when contact information, email addresses, job changes, and other information become outdated
• Incomplete data, where missing fields or partial records are present, impacts the accuracy of predictive scoring models
• Multiple entries of the same data can skew the scores
• Over-automation of data can lead to data detachment where errors and biases are unchecked w/out human intervention
• Inaccurate data can lead to false assumptions within the scoring
• Historical data can reflect biases that machine learning amplifies, potentially leading to the overvaluation of certain demographics and channels
• Collecting and using data without proper consent can violate GDPR and CCPA regulations, potentially leading to legal and reputational damage

To help maintain data quality, it's important to recognize and follow these top seven best practices for clean data:

1. Perform regular data cleansing, including removing duplicates, updating outdated information, and completing missing fields
2. Verify data sources using tools and processes at the data entry points
3. Integrate data sources by consolidating data from our CRM, marketing automation, and external sources to create a unified view of the data
4. Incorporate human touch validation to catch nuances that AI may miss
5. Embrace first-party and zero-party data where a more mutual connection is already established
6. Monitor data health and KPIs to ensure data quality, and conduct periodic audits
7. Educate your teams on the importance of data hygiene and proper data entry

Before taking a deep dive into predictive analytics for your lead generation campaigns, it's wise to take a step back first and assess the health of your data. Ask your team the following:

‍Is our information accurate, current and detailed enough?

Are all our sources—CRM, marketing tools, social media, etc. talking to each other and feeding into one accessible system?

Are we capturing those subtle signals (i.e., intent data) that indicate when a prospect is ready to make a purchase?

Is our data setup secure and compliant?

Remember: Predictive analytics can be your business' conductor, orchestrating your lead generation with precise targeting of prospects that will convert to sales. However, it requires predictive scoring, data accountability, and team collaboration with human oversight to deliver consistent, measurable success.

Ready to wave the baton and take your lead generation to new heights?

Reach out to our VP of Strategic Partnerships, Lauren Harber, today!