Splattr is built for any sales team that wins by reaching the right people with the right message, from founders and individual reps to full revenue teams. It's especially powerful for considered, research-heavy sales like consulting, staffing, and IT services, but customers across a wide range of industries use it to prioritize their market and personalize outreach at scale.

How is Splattr different from Apollo, ZoomInfo, Seamless, Clay, and Instantly?

Those tools are mostly contact databases and sending engines. They hand you names, emails, or a way to blast them. Splattr sits a step earlier: it's a targeting and scoring engine that figures out who is most likely to buy right now and why, then tells you how to start the conversation. Instead of a generic ICP list, Splattr researches every prospect through the lens of what you actually sell, layering in buying signals, hiring data, and tech stack to score and rank them.

How does Splattr find and score the right prospects?

You train an agent on what you sell, and Splattr scores prospects across your market by analyzing publicly available data like buying signals, hiring and job-posting activity, and technology footprint, all measured against your specific offer. Each prospect gets a score plus clear reasoning for why they ranked where they did, so you can prioritize with confidence.

Can I customize how prospects are scored?

Yes. Scoring is driven by the agent you train on each offer, so the criteria reflect your product, your differentiators, and your ideal buyer, not generic out-of-the-box filters. Companies selling multiple products can run a separate scoring lens for each offer.

What intelligence do I get on each prospect?

Every prospect comes with a score and the reasoning behind it, specific leverage points for your outreach, detected business signals (financial, strategic, and hiring/job changes, with sources), hiring metrics, and the company's technology footprint. It's the research that used to take 30+ minutes per prospect, ready in seconds.

Does Splattr integrate with my CRM and outreach tools?

Yes. Splattr offers a direct HubSpot integration so your scored prospects flow straight into your CRM, with Salesforce support coming soon. You can also export any list to CSV to use in other outreach tools.

How does pricing work?

Splattr is $12 per seat per month to keep your account active, and everything else runs on credits, so you only pay for the prospecting you actually do. You can go fully pay-as-you-go at $0.0299/credit, or save with a credit bundle (down to about $0.017/credit). All features are included on every plan.

What does each action cost?

Different actions use different amounts of credits: Find & score a prospect — 8 credits Look up a LinkedIn profile — 4 credits Find contacts at a company — 2 credits Research report — 8 credits Company report — 20 credits Email lookup — 6 credits Phone lookup — 15 credits Chatting with Splattr's AI assistant also uses credits, based on how much you use it.

Is there a free trial, and how do I get started?

Yes. You can score your first prospects free, no credit card required. Just tell Splattr what you sell, answer up to nine quick questions to train your agent (about 3 minutes), and you'll have scored, prioritized prospects in under 10 minutes.

How quickly will I see results?

Most users go from signup to their first qualified, scored prospects in under 10 minutes, and start personalizing outreach the same day.

How is my data handled and kept secure?

Splattr scores prospects using publicly available data, and we treat your account data as your own. We don't sell your data or use your content to train models that benefit other customers. Your data is hosted on Amazon Web Services in the United States, encrypted in transit and at rest, with role-based, least-privilege access controls. Payments are handled by our PCI-compliant processor, and we never store your card details. Full details are in our Privacy Policy and Data Processing Addendum.

Can my whole team use Splattr together?

Yes. Teams get a shared full-team view and can share campaigns across users, so everyone works from the same prospecting engine. On the Business plan you also get a shared credit pool, per-user spending controls, and dedicated support.

A Hiring Signal Is Meaningless Without the Baseline

Signal data is only useful inside context. On its own, a signal is just as likely to mislead you as to help you. Say a prospective account posts five new marketing roles. If you sell something related to marketing, that looks like a clear signal worth acting on. Reach out now, they are clearly expanding. Maybe. Or maybe not. ## The questions a snapshot cannot answer Before you treat those five roles as a reason to reach out, you have to ask: - Do they hire five marketing people every quarter? Every year? - Is there an actual change in the rate at which they hire for marketing, or is this normal for them? - Is this a new expansion that could be signaling a much bigger transformation inside the company? You cannot answer any of that from the job postings that are open today. Today's postings are a snapshot. The snapshot tells you what is happening; it does not tell you whether it is unusual. ## History is what makes a signal mean something To interpret the five roles, you need the last few years of that company's hiring, not just this month's. With the full history, the same five postings become readable. If they hire five marketing people every quarter, this is routine replacement and not a signal at all. If they have never posted more than one marketing role at a time and suddenly there are five, that is a real shift in how they are spending, and it is worth your attention. A handful of open roles tells a fraction of the story. The history is what tells you whether you are looking at business as usual or a genuine change. A one-off data point cannot do that, no matter how promising it looks. ## The point Never act on a signal in isolation. The number of open roles, the funding event, the new hire, none of it means anything until you know what normal looks like for that specific company. Get the baseline, then decide whether what you are seeing is noise or a reason to call.

Put this into practice