Using prospect data to shape email campaigns

Struggling to turn window shoppers into customers? Let’s talk zero-party data—your untapped goldmine for skyrocketing conversions. Here’s the deal: most brands settle for collecting just an email and name on their pop-ups. That’s fine… if you like leaving money on the table. But when you dig deeper—asking the right questions to understand the needs of your traffic—you unlock the power to craft personalized experiences that make buying your product feel like a no-brainer. It’s not just about gathering data; it’s about context. Think about it: a generic email might say, “Hey, check out our skincare line.” But if you know your prospect’s biggest concern is aging gracefully, your message transforms into, “Here’s the secret to looking radiant at any age.” Boom. Relevance = revenue. The magic lies in pairing this data with strategic email flows. By tailoring messages to match each prospect’s stage in their journey, you’re no longer just selling, you’re solving their exact problem. The formula is simple: ask specific, easy-to-answer questions, collect actionable insights, and use them to deliver value. Whether it’s a product recommendation or a perfectly timed follow-up, zero-party data lets you meet your customers where they are—and guide them where you want them to go.

Years doing cold outreach taught me this: Bad segmentation will break your campaigns Look, I get it—spray and pray is easy. It’s low maintenance, and sometimes it even works. But here’s the problem ❌ Low reply rates ❌ Risk of burning your dream clients ❌ Wasted email volume on unqualified prospects The result? Fewer meetings booked per week. Here’s what to do instead: 𝟭. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗵𝗶𝗴𝗵-𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁 𝗹𝗶𝘀𝘁 Scrape your Total Addressable Market (TAM) using Apollo.io (or similar). Then, upload the data into Clay for deeper segmentation. 𝟮. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗯𝘆 𝗳𝗶𝗿𝗺𝗼𝗴𝗿𝗮𝗽𝗵𝗶𝗰𝘀 Break your list down by: ✅ Industry ✅ Seniority ✅ Revenue* ✅ Company size ✅ Role/Department To get precise revenue data, use waterfall enrichment: 🔹 Clearbit 🔹 HG Insights 🔹 RocketReach 🔹 People Data Labs 🔹 Owler - A Meltwater Offering This helps you focus on high-probability prospects who are more likely to convert. 𝟯. 𝗚𝗼 𝗱𝗲𝗲𝗽𝗲𝗿 𝘄𝗶𝘁𝗵 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Leverage Claygent to segment based on unique attributes: 🔍 Does the company offer Buy Now, Pay Later? 🔍 Are they SOC II, GDPR, or ISO 9001 compliant? 🔍 Do they have a podcast? Use yes/no questions or multiple-choice (max 3 options) to improve accuracy. The goal? Gather enough intelligence to anticipate their pain points, and solutions before even reaching out. 𝟰. 𝗨𝘀𝗲 𝗰𝗮𝘀𝗲 𝘀𝘁𝘂𝗱𝘆-𝗯𝗮𝘀𝗲𝗱 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 Ocean.io helps you find hundreds of companies similar to your highest-paying clients, while a simpler (but still effective) approach is to segment by industry and refine it over time. 𝟱. 𝗦𝗲𝗴𝗺𝗲𝗻𝘁 𝗯𝘆 𝘃𝗲𝗻𝗱𝗼𝗿𝘀 & 𝘁𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸 Another powerful way to qualify leads is by the vendors they use: ⚡ BuiltWith – See what technologies are installed on a website. ⚡ ScrapeLi – Check if they follow a certain company on LinkedIn. ⚡ PredictLeads – Scrape employee certifications & job postings to understand what software they’re using. At the end of the day, better segmentation = better results. 𝗤𝘂𝗶𝗰𝗸 𝗿𝗲𝗰𝗮𝗽: Scrape a lead list Segment by firmographics Use Claygent for advanced segmentation Use case study-based segmentation Use vendor-based segmentation P.S. Are you implementing these methods?

Founder: "We're getting 0.3% reply rates... What are we doing wrong?" Me: "You're not using the right data." After optimizing outbound for 120+ companies, here's the data framework that gets 3-4% reply rates: Most teams only use one type of data for prospecting. They miss 80% of their opportunities because they're not combining data sources. Here's the 3-layer data system that actually works: 1. FIRST-PARTY DATA → "Who's visiting your website" This is data you collect directly from your own customers and prospects. Definition: Information gathered from your website, product, and direct interactions. The opportunity: Not everyone fills out a form, but that doesn't mean they're not interested. Examples: → Anonymous website visitors checking pricing pages → Product users exploring features without converting → People engaging with your LinkedIn content consistently Tools: PostHog Mixpanel Hotjar | by Contentsquare for website behavior, Common Room Trigify.io for social engagement. 2. SECOND-PARTY DATA → "Champion job changes" This is another company's first-party data shared with you through partnerships. The opportunity: Someone loved your product at their old company. They just switched jobs. Examples: → Partner companies sharing contact updates → Integration partners revealing mutual prospects → Review platforms showing who's evaluating competitors Tools: G2 Capterra for review insights. (soon ColdIQ 👀 ) 3. THIRD-PARTY DATA → "Research at scale" This is data aggregated and sold by external providers. Examples: → Companies hiring for specific roles (buying signals) → Funding announcements and growth indicators → Technology stack changes showing readiness to buy Your approach: Filter for buying signals, enrich contacts, and segment your list. Tools: Clay workflows with BuiltWith, Crunchbase and Apollo for example. The difference this makes: 0.3% reply rates → 3-4% reply rates Same effort, 10x better results. Each data source requires different messaging strategies. First-party: "We noticed you've been exploring..." Second-party: "Your partner mentioned..." Third-party: "Based on your recent growth..." Which data source are you using right now? P.S. Want the exact workflows for each data layer? I break down systems like this in our newsletter: https://lnkd.in/dxFJTPXm

Have you implemented arguably the most important concept of digital marketing into your campaigns? The secret to truly effective digital marketing lies in one often-overlooked concept: leveraging your customer data for personalization. Over the years, we've seen clients at JUICE onboard running digital campaigns that looked great on paper but weren’t delivering results. They had the right tools, the right platforms, and even the right content, but something was missing. That’s when we introduced them to the power of using customer data to personalize their strategies effectively. Utilizing customer data to personalize marketing efforts transformed our clients' approaches. Here’s how: - Segmented Email Campaigns: Instead of sending generic emails to their entire list, our clients started segmenting their audience based on behavior and preferences. This increased open rates and engagement significantly. - Dynamic Content: We helped them implement dynamic content on their websites and landing pages that changed based on who was visiting. This made the content more relevant and engaging. - Personalized Ads: Using customer data, we tailored ad campaigns to target specific audience segments with messages that resonated with their needs and interests. 🌱 What's the science behind personalization? Research shows that leveraging customer data for personalization is crucial for digital marketing success. According to a study by Epsilon, personalized emails deliver 6x higher transaction rates. Additionally, 80% of consumers are more likely to make a purchase when brands offer personalized experiences, as reported by Econsultancy. Digital marketing experts like Neil Patel and Ann Handley emphasize the importance of personalization. Neil Patel says, “Personalization is the key to marketing success. It’s about understanding the customer’s needs and delivering tailored experiences.” Ann Handley, a pioneer in digital marketing, also highlights, “Content that’s personalized to the audience is not just more engaging—it’s more effective.” 🚀 How do you actually do this? - Segment Your Audience: Use tools like CRM and email marketing platforms to segment your audience based on behavior, demographics, and preferences. - Implement Dynamic Content: Use personalization tools to create dynamic content that adapts to different users on your website and landing pages. - Personalize Email Campaigns: Tailor your email marketing campaigns to address the specific needs and interests of different audience segments. - Use Behavioral Data: Analyze customer behavior data to understand their journey and preferences, and use this information to personalize your marketing messages. - Test and Optimize: Continuously test different personalization strategies and optimize based on performance data.

Personalized emails can increase open rates by up to 50% – here's how to make it work for your brand 👇 1) Segment your subscribers: Differentiate your email list based on customer behavior, such as purchase history, browsing habits, and engagement with previous emails. → Segment customers who have purchased within the last 30 days from those who haven't purchased in over six months. Tailor your messaging to re-engage the latter with special offers or reminders about the benefits of your products. 2) Personalize subject lines: Create subject lines that include the recipient's name or reference past purchases. Studies show that personalized subject lines can increase open rates by 26%. → Instead of a generic "Check out our new arrivals," try "John, new arrivals just for you!" or "Loved those shoes? Here are matching accessories!" 3) Tailored content: Use dynamic content blocks to personalize email content for different segments. For example, recommend products based on past purchases or show relevant content based on browsing behavior. → For a customer who frequently purchases sportswear, include recommendations for new sports equipment or apparel. If a shopper has been browsing a particular category, such as electronics, highlight related products or special offers in that category. 4) A/B testing: Continuously A/B test your email campaigns to find the most effective personalization strategies. Test different variables such as subject lines, content layout, and send times. → Test two versions of an email - one with a personalized subject line and one without. Compare open rates and use the winning subject line strategy in future campaigns. Similarly, test different call-to-action (CTA) placements to see which drives more clicks. 5) Analyze and adjust: Analyze the performance of personalized emails and adjust your strategy based on what you learn. → Monitor metrics such as open rates, click-through rates, and conversion rates for your personalized emails. If a particular type of personalized content consistently performs well, include more of it in future campaigns. Conversely, if a strategy is underperforming, adjust your approach based on the data. 🤔 How have you used personalization in your email campaigns, and what results have you seen?

Many argue: Winning DTC brands thrive on smart strategies. But here's the truth: They leverage data to win. Sounds complex? It's actually straightforward. Successful DTC brands use: ↳ Hyper-personalized customer journeys for each sub avatar ↳ Data collection from the moment someone clicks an ad ↳ Data to enhance email/SMS performance ↳ Data enrichment platforms to boost email flows My agency has helped DTC brands generate over $110M in added email revenue. Here’s how we do it: ☑ Personalized Journeys: Personal experiences for each customer segment. ☑ Smart Data Collection: Gather data from the first click to segment accurately. ☑ Personalized Communication: Use collected data to improve email/SMS effectiveness. ☑ Supercharged Email Flows: Leverage data enrichment platforms for better results. Here's why these tactics matter: Improved customer engagement • Higher conversion rates • Increased retention • Better customer insights • More effective marketing campaigns What does it mean to use these strategies? You create a data-driven approach when you: ☑ Personalize Customer Journeys: Craft unique experiences for different segments. ☑ Collect Data Early: Start gathering data from the first interaction. ☑ Use Data Wisely: Enhance your communication strategies with insights. ☑ Enrich Your Data: Use platforms to add depth to your customer profiles. ☑ Optimize Campaigns: Continuously improve based on data feedback. ☑ Focus on Retention: Keep customers coming back with tailored experiences. ☑ Drive Revenue: Boost sales through smarter marketing efforts. Using data isn't just a tactic. It's a commitment. A commitment to understanding your customers. To using insights to drive success. Lead with data in mind. And higher email/SMS revenue will follow.