Project executed by the Akaen team.
At Akaen, we identified a specific problem in our own sales process: prepare each lead well before first contact and then maintain disciplined follow-up. Researching each company, finding relevant contacts, understanding the account and turning that context into useful use cases took time and depended too heavily on manual work.
The problem also affected pipeline quality. Sales context was scattered across notes, links and individual memory; stage changes did not always reflect a lead’s actual status; and follow-up relied too heavily on manual reviews or ad hoc reminders.
Executive summary
About Akaen
Akaen designs automations, integrations and AI solutions for business operations. Our sales process is consultative: it requires us to understand each account quickly, develop realistic value propositions and follow up consistently. It made sense to apply internally the same approach we offer customers: less administrative work and more useful context for taking action.
The challenge: too much manual preparation and follow-up that did not scale
Each new lead required a useful company profile before it could be prioritised: sector, size, operations, likely technology stack, key contacts and use cases where Akaen could add value. Without automation, much of this work was rebuilt account by account.
Then came the second bottleneck: follow-up. Once a conversation started, the team had to keep stages, next actions, open opportunities and pending alerts up to date. Relying too heavily on manual updates risked turning the CRM into an incomplete activity log instead of a tool for executing sales.
The solution: our own CRM designed to research accounts, prioritise leads and drive sales activity
Akaen built its own operations-focused system. Each lead enters a workflow that automatically enriches the account with business context, relevant contacts and use cases tailored to its sector and size. This creates a stronger foundation before the first sales contact.
We also automated the sales lifecycle. The CRM moves leads between stages based on events, updates opportunities, issues follow-up alerts and provides operational views by salesperson or team. The goal was to make the next best action visible in each account.
Automated Processes (5 key flows)
1. Automated account research
The Problem: Analysing a new company meant consulting several sources and manually reconstructing its basic context before assessing the fit.
Transformation: The CRM automatically generates an enriched account profile with relevant information and useful signals for sales prioritisation.
2. Identification of key contacts
The Problem: Finding relevant contacts and deciding whom to approach first took time and did not always follow consistent criteria.
Transformation: The system identifies and organises key account contacts so the salesperson has a useful starting point from the outset.
3. AI-generated use cases by sector and company size
The Problem: Determining which Akaen solutions suited a particular company depended heavily on manual preparation and individual experience.
Transformation: The CRM proposes value assumptions and specific use cases for the account based on its sector, size and operational context, providing much more relevant outreach messages.
4. Lead and opportunity lifecycle automation
The Problem: Moving leads between stages manually and keeping the pipeline up to date added administrative work and reduced the quality of the sales funnel.
Transformation: Lead and opportunity stages update automatically based on events, responses and defined sales rules.
5. Alerts and operational views by salesperson and group
The Problem: Daily follow-up relied too heavily on memory, manual pipeline reviews or individual discipline.
Transformation: The system generates follow-up alerts and views by salesperson, team or funnel status, keeping pending actions visible and prioritised.
Operational comparison
- • Account research assembled manually from multiple sources.
- • Sales context scattered across notes, links and tacit knowledge.
- • Follow-up dependent on individual discipline and periodic reviews.
- • A pipeline at risk of drifting from the real status of opportunities.
- • Each lead is already enriched with actionable context.
- • Contacts and use cases are structured within the CRM.
- • Stages advance through events and rules, rather than relying solely on manual updates.
- • Pending follow-ups become visible, shared and easy to prioritise.
The Impact
The system does more than save isolated tasks: it improves the entire sales process. The team works with better-prepared accounts, follow-ups no longer get buried, and the pipeline becomes an execution tool rather than merely a reporting tool.
- Less preparation per account: part of the research no longer needs rebuilding from scratch.
- Greater consistency across sales: the accounts are analysed with a more consistent level of context.
- Stronger follow-up: pending actions are triggered and visible before they fall behind.
- Better quality of the pipeline: the phases better reflect the actual state of each opportunity.
Operational results
- Faster sales preparation: accounts reach salespeople with more context from the start.
- Better targeted messages: outreach starts from more concrete hypotheses and use cases.
- A CRM that supports daily work: it moves from a partial history to a living operational tool.
- Internal scalability: growing sales volumes do not bring a proportional increase in manual work.
Conclusion
“A CRM should do more than record what the sales team has already done. It should prepare the next best action with the right context.”
Want to apply this approach to your own sales, service or back-office operations? .