gastromatic: every enquiry reaches sales fully prepared.
At a glanceStarting point
Names in the database that no one can reach any more.
gastromatic faced several challenges in sales. The extensive database in HubSpot, holding more than 30 percent of the relevant market, was only of limited use because of outdated and incomplete entries. „Früher hatten wir oft Namen in HubSpot, die nichts mit den tatsächlichen Ansprechpartnern zu tun hatten oder Personen, die nicht mehr im Unternehmen sind", Christian Fuchs explains. The manual research and preparation of lead information cost the sales development representatives (SDRs) a great deal of time that was then missing for valuable customer conversations. At the same time, the barrier to cold outreach was high when only little information about potential customers was available.
Solution
An AI employee that takes on the research before the call.
Christian Fuchs came across scoreprise.AI through LinkedIn. In the first conversation with Niclas Barthélemy (CEO and Co-Founder of scoreprise.AI), the pragmatic approach was convincing: „Niclas hat das sehr verständlich auf konkrete Anwendungsfälle heruntergebrochen. Das hat mir geholfen, den Nutzen für Gastromatic direkt zu erkennen."
An AI employee for lead intelligence (called Carl in the project) supports the sales team with lead research, data enrichment and conversation preparation. It searches the internet in a targeted way for potential customers, for example golf and hotel resorts, gathers information about contacts and prepares detailed profiles in HubSpot.
Research
Target customers from the web
The AI employee searches the internet in a targeted way for suitable businesses, for example golf and hotel resorts, and gathers the associated contacts.
Enrichment
Profiles in HubSpot
The findings become detailed profiles in the CRM. Outdated and incomplete entries are replaced in the process.
Conversation preparation
Openings instead of a cold start
For each contact there are openings drawn from LinkedIn activity and company news, so the first conversation starts prepared.
The aha moment
„Den größten Aha-Moment hatte ich eigentlich schon zu Beginn, wo wir den ersten Test-Account mal gesehen haben und gesehen haben, wie Carl eigentlich arbeitet und wie der so Daten aufbereitet […] das gibt einem halt so viele Informationen, die man normalerweise wirklich nur über manuelle Recherche rausbekommt“
In the first test account it became visible what the AI employee brings together: posts on LinkedIn, topic interests, the path from apprentice to head of. Details that previously cost a separate piece of research for every approach.
Result
The conversation begins with what matters to the customer.
The introduction was received consistently well within the team. The SDRs benefit from noticeably better ways into conversations: „Die Hemmschwelle, jemanden kalt anzurufen, sinkt erheblich, wenn man weiß, mit wem man spricht. Wenn ich einen LinkedIn-Post oder eine aktuelle Neuigkeit zum Unternehmen nennen kann, wirkt das viel persönlicher und aufmerksamer", Christian Fuchs explains.
Data quality has improved noticeably, and the SDRs can concentrate on valuable tasks instead of time-consuming research. A small task force in the sales team looks after quality assurance and is in weekly exchange with scoreprise.AI in order to keep improving the process.
„Je genauer ich Carl sagen kann, wonach er suchen soll, desto besser sind die Ergebnisse. Für uns war das ein wichtiger Schritt, um mit den vorhandenen Ressourcen effizienter zu arbeiten. Carl ist dabei mehr als nur ein Tool: Er ist ein echter Kollege, der das Team spürbar entlastet.“
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Cancellable monthly · Operated in Germany