Prospecting data refers to information collected about potential customers that businesses can use to find, qualify, and turn new prospects into leads and sales. For business-to-consumer (B2C) companies looking to expand their customer base, prospecting data is an invaluable asset.
By leveraging data on prospects’ contact details, demographics, interests, and buying intent, B2C companies can precisely target their outreach, advertising, and messaging to resonate with potential customers. This helps generate more qualified leads that convert at a higher rate compared to non-targeted prospecting efforts.
The key benefit of using prospect data is that it enables B2C companies to reach prospects they otherwise may not have known about or been able to identify. Prospect data helps uncover net-new potential customers across existing, adjacent, and entirely new target markets.
With high-quality prospecting data integrated into sales and marketing workflows, B2C companies can expect to generate 20-30% more prospects and 2-3x higher conversion rates from outbound prospecting activities. The ability to zero in on the right potential customers is why prospect data should be a foundational component of any B2C customer acquisition strategy.
Types of Prospecting Data
Prospecting data comes in many forms, all of which can help B2C companies identify and target potential new customers. Here are some of the main types of data to leverage:
- Contact data – This includes details like names, phone numbers, email addresses, and mailing addresses. Contact data enables a company to directly reach out to prospects through calls, emails, and direct mail.
- Demographic data – Details like age, gender, income level, education, marital status, and more. Segmenting an audience and creating targeted messaging relies heavily on demographic data.
- Firmographic data – Information on a prospect’s company, like industry, number of employees, location, department, job title and role. This helps segment business prospects specifically.
- Interest data – The hobbies, preferences and interests of prospects. This type of data allows for personalized, relevant messaging tailored to what resonates most with prospects.
- Intent data – Behavioral signals that indicate interest or intent to buy something. This could include website visits, content downloads, search queries, and more. Intent data identifies high-quality leads ready to buy.
- Social data – Details gathered from social media profiles, like connections, posts, and group memberships. Social data provides insights to inform outreach and relationship-building.
The right mix of these prospect data types enables B2C companies to reach precisely the new customers they want to target, and craft messaging that aligns with their needs and interests. Segmenting and personalizing outreach boosts response rates and conversions.
Sourcing High-Quality Prospect Data
Prospect data comes in many forms, but not all prospect data is created equal in terms of accuracy and relevance. Here are some of the top sources for obtaining high-quality B2C prospect data:
Paid Data Sources
- Data brokers – Companies like Acxiom, Experian, and Infogroup compile vast databases of consumer contact info, demographics, interests, and behaviors. This data can be licensed to help find targeted prospects.
- Intent data – Providers like Bombora and Demandbase sell data based on business interest and research signals, to identify prospects actively exploring products/services.
- Contact lists – Specialized list providers sell access to targeted prospect contacts, like small business owners in a certain industry or location.
Free Data Sources
- Business directories – Resources like Manta and Crunchbase provide searchable company and contact info to identify prospects.
- Web research – Company websites and social media pages can provide useful data on prospects.
- Trade show lead lists – Many industry events will sell or provide their registration contact data.
- Business association directories – Organizations like chambers of commerce may provide member directories to aid prospecting.
Smart Prospect Data Methods
- Review your existing CRM data to identify customer traits and behaviors that indicate good prospects for upsell/cross-sell.
- Supplement your owned data with demographic, firmographic, and technographic data purchases targeted to your ideal customer profile.
- Prioritize prospects with high research activity and engagement with your brand and content.
- Look for prospects similar to existing customers via social/web data to find lookalike targets.
- Partner with data providers who allow transparent sourcing and screening to avoid outdated or irrelevant contacts.
The key is using a blend of paid and free high-quality prospect data sources to maximize your reach and efficiency in identifying potential new customers. Target and qualify leads carefully to ensure prospecting efforts remain relevant and effective.
Using Prospect Data to Generate Leads
Once you’ve compiled a list of robust prospect data, it’s time to put it into action to generate and qualify new leads. Here are some of the most effective tactics for leveraging prospect data:
Email Outreach
Targeted email outreach is one of the top ways to utilize prospect data for lead gen. Using detailed contact info and demographic data, you can craft personalized emails that will resonate with different prospect segments. Tailor your messaging to their interests and needs. Prospect data enables you to personalize emails at scale.
Direct Mail
Prospect postal address data opens up direct mail as an option. Create a well-designed and relevant mailer campaign and send it to your targeted list of prospects. This physical touchpoint can capture their attention in their mailbox. Follow up with additional direct mail as part of your nurture stream.
Social Media Ads
Detailed demographic and interest data on prospects allows you to target Facebook, LinkedIn, and other paid social media ads. Serve these ads to ideal customer profiles most likely to convert to leads based on your ideal customer profile. Social media is a cost-efficient way to generate leads from prospect data.
Integrating Data into Your Workflows
To fully capitalize on prospect data, integrate it into your existing sales and marketing systems and workflows. Add the data into your CRM and map it to the appropriate leads and contacts. Import email addresses into email marketing software and set up automated drip campaigns. Sync prospect data with marketing automation platforms to nourish and score leads over time. This will maximize the value of prospect data.
Measuring the ROI of Prospecting Data
Using prospecting data can significantly increase lead generation for B2C companies, but to determine if it’s worth the investment, you need to properly track metrics and measure the ROI. Here are some tips on calculating the return from prospect data:
- Establish metrics to benchmark. Before starting any prospecting initiatives, determine key metrics you want to track like cost per lead, sales opportunities created, deal size, etc. Use current lead gen numbers as a baseline to compare against.
- Track source of leads. Ensure your CRM or marketing automation system can track leads back to the original prospect data source. This allows you to see which datasets or lists generate the most valuable leads.
- Calculate cost per lead. Add up the costs spent on purchasing prospect data and then divide it by the number of leads generated from that dataset. Compare to your benchmark CPL before using prospect data.
- Measure deal size. Analyze if prospects from purchased data convert into larger deals versus other lead sources. Larger deal sizes can offset higher CPL from prospect data.
- Consider lifetime value. Don’t just look at the first deal. Evaluate the total value of a new customer relationship over several years. This gives a better ROI picture.
- Optimize over time. Continuously refine prospecting criteria to only target high-value segments. Stop using data that doesn’t generate sufficiently profitable leads.
By regularly assessing prospecting data ROI, you can concentrate spending on the datasets and tactics that provide the highest return. Over time, you can significantly scale lead generation while keeping CPL and conversion costs efficient.
