To make social proof more potent, Ramp's data team developed a similarity model. For any given prospect, the model identifies the most similar current customers. This information is then piped into ad platforms, website personalization tools, and the CRM for sales to use on calls.
Related Insights
We are most influenced by people like ourselves. Instead of general popularity claims like '10,000 users,' specify how many customers are in the user's specific state or city. This tailored social proof creates a much stronger connection and is more persuasive.
Startups should stop building customer personas on assumptions and surveys. Instead, use AI to analyze real-time behavioral data, creating dynamic profiles that update automatically. This shifts marketing from targeting who you think customers are to who they actually are based on their actions.
Instead of waiting for intent, Demandbase proactively builds future pipeline by scoring cold accounts. They create lookalike models based on their best customers and invest marketing spend against high-scoring cold accounts, anticipating they will enter a buying cycle in 9-12 months.
Instead of guessing who to target, review your past positive interactions. Identify common characteristics among responsive and appreciative clients to build a data-informed profile of who you should be approaching next.
Stop defining your Ideal Customer Profile with abstract firmographics. Instead, feed context from your best closed-won deals into an AI and ask it to find public data that signaled their specific pain *before* they engaged you. This reverse-engineers a truly effective, data-driven targeting model.
Executive teams often create an ICP based on a 'wishlist' of big logos. The most accurate ICP is actually found by analyzing your first-party CRM data. Examining patterns across both close-won and close-lost deals reveals surprising truths about which customer segments are actually the best fit for your solution.
Generic social proof like "1 million customers" is minimally effective. The key is to tailor the message to the user's identity. We are most influenced by people like ourselves, so messages like "other doctors in Sydney" or "your neighbors" have a much stronger impact.
Tailor social proof to the buyer's journey stage. Top-of-funnel prospects need quick, quantitative signals of trust like star ratings and review volume. Lower-funnel and retargeting audiences, who are closer to a decision, are more influenced by specific, qualitative quotes.
Instead of guessing at marketing copy, build an AI model of your ideal customer. By feeding it internal data like call transcripts and external data like forum posts, this "digital twin" can review and rewrite your marketing materials using the customer's exact language.
To make outbound effective, UserGems combines multiple signals into one message. Instead of a generic cold email, they'll reference a prospect's new job, a former colleague who is a customer, and a past conversation with their company. This multi-layered personalization drives higher reply rates.
