To run a sales process optimally, you need to understand the different customer journeys that lead to a sales. This will differ from business to business, as all elements need to be taking into account. And while lots of companies start with assuming an ideal path for customers to traversing, from being lead to becoming a paying customer, the reality shows that this assumption is often wrong, or at least is not unilaterally correct.
Most often, different customer persona’s may show interest in your product for different reasons, will be looking at different content, may react to different Call-To-Actions (CTAs) and may submit their details on different contact forms at different ideal moments.
The better you understand the different persona’s, interests, moments and paths, the more personal you can guide them through the sales process, and the more you will be selling.
So it all comes down to getting to know each lead as well as possible. A first great step is to categorise your leads into different persona’s, typically defined by different interests for different USPs. Depending on the type of products and business, some companies may also chose to define persona’s by company size, by location, by personal interpersonal behaviour, etc... In any of those cases, measuring what leads are doing is vital to detecting ideal paths.
Based on these paths, interest, and moments, you can now decide to split your different sales processes into different sub-stages, each being handled by sales specialists for a specific sub-stage. Examples of sub-stages are sales qualification, technical buy-in, business-buy-in, etc... This is often done by one person in smaller companies, yet larger sales teams often organise themselves accordingly in smaller groups to handle their each sub-stage. Either way, having proper customer data is crucial in understanding the specifics of each lead in their current stage, and in bringing these leads to a next stage.
journy.io collects events, ad campaigns, channel information, devices, locations, timings and everything which is done throughout the customer lifecycle. Including what happens during trial. More precisely, we collect every event with contextual data from every possible source, unify every sub-journeys from every device and browser to get a full timeline of everything every user from every account is doing.
So, if you want to measure what each persona is doing during each sales stage, to later use this to detect which persona your lead actually is, journy.io would be your ideal tool. Even better actually, journy.io does the full Persona detection for you!
On top of that, our journey-comparing engine provides your sales teams (or sub-stage teams) both native app data, as well as contextual and behavioural intelligence derived from that, so they can take more personal actions, right at the moment that counts.
Customer-facing teams at SaaS companies need clear insights on who their customers are, and what they’re doing on your platform. 🙌 With stage view, journy.io provides a SaaS growth pipeline, with accounts/users clearly ordered by lifecycle stage, and which includes key details, from health to triggered PLG signals. 💡
Growth teams at SaaS companies need clear insights on who their customers are, and how they differ with e.g. those who didn’t convert. By analysing data from across an entire stack, from CRM, Marketing Automation, and other engagement platforms —combined 🙌— they are now able to easily determine trends in customer segmentations and aggregations.
Customer teams need product usage insights. To that end, dev teams are being asked maintaining non-platform-critical features. A better approach is to simply send raw events and metadata onto a secure data pipeline, and have a customer data platform compute key metrics!
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