MQLFlow

MQLFlow Saves Boutique Search Firm Hundreds of Hours with AI

Custom integrations and AI that saved weeks of work each month

We joined a biotech search firm's CRM to its email, LinkedIn and website, automated follow-ups on any unanswered email, and built AI that wrote its social posts and case studies.

Topics

Results

  • 90+1

    hours a month gained to focus on recruitment

  • 21

    automation ideas mapped and costed before the build

Services we delivered

AI consulting

AI consulting that mapped how the firm worked, costed every automation idea and set the build order.

  • Solution design: how each automation would work, specified and scoped before the build
  • Business development and CRM processes mapped as workflow diagrams
  • Hours saved and first-year return for each time-saving automation, and build effort for every idea
  • Software recommended and costed before anything was bought

Systems and data integration

Systems and data integration that joined Manatal CRM to Outlook, LinkedIn and the firm's website, so records filled themselves in.

  • Companies and contacts enriched from external data as they were added
  • Contacts added from LinkedIn in one click, with their company created
  • Website enquiries qualified, with their marketing source recorded
  • Email logging set up between Outlook and Manatal, so conversations were kept on each contact's record

Business process automation

We automated the firm's email follow-ups and marketing end to end, with AI writing and illustrating the content.

  • Follow-ups sent automatically from the founder's own mailbox whenever an email went unanswered
  • Branded LinkedIn carousels and case studies written and illustrated by AI
  • Review requests after every placement, with AI-written replies to positive reviews
  • A re-engagement campaign that invited past contacts back into conversation

The brief

AG Consulting is a UK-based, international executive search firm specialising in biotech and life sciences. The founder wanted to grow the firm without working longer hours, so his time had to go on finding clients and filling roles, not admin.

But admin got in the way: adding a contact from email or LinkedIn took several steps, company details were researched by hand, and every unanswered email needed chasing. He also wanted fuller records for every conversation, to reopen conversations with past contacts and to raise the firm's profile on LinkedIn, without it taking up his time. His CRM's built-in automations were mainly for candidate work, so the business development side needed a developer to build custom integrations. We started with an AI and automation strategy, then designed and built our recommended workflows.

The CRM automations speed everything up, reduce my admin, and continuously improve the quality of my data. I can't recommend MQLFlow enough for any business looking to take advantage of AI.
Ivan GitardiIvan GitardiFounder, AG Consulting

Considerations

We designed the automations around what mattered most to AG Consulting.

  • Custom integration for business development. Although Manatal has an API, its built-in automations were focused on candidates, so the integration, logic and data mapping between the CRM, Outlook, LinkedIn and the website had to be custom designed and built.
  • Capture before contact. Manatal logged email conversations only for contacts already in the CRM, so adding a contact had to be quick enough to do before the first email.
  • Only the right leads in. Website enquiries had to be checked against the firm's ideal client, by industry, country, company size and job title, before they reached the CRM.
  • On brand, in his voice. Every AI-written post and case study had to match the firm's branding and the founder's tone of voice, so the templates and style were agreed with him first.
  • Relationships protected. Contacts the firm wanted left alone were held back from the re-engagement campaign.

Approach

We designed the whole plan before building anything, so the founder could see what each automation would give back before he invested.

  • Every process mapped. We mapped how the firm found clients, ran its outreach and kept its CRM up to date, and drew each proposed automation as a workflow diagram.
  • Every idea costed. Each idea came with its build effort, the software it needed and what that would cost a month, and each time-saving automation with the hours it would save and its first-year return.
  • Time savers first. The CRM and email automations needed less building and would give hours back straight away, so they went in before the marketing.
  • Built with the founder. We met every fortnight, he reviewed each automation before it went live, and video walkthroughs showed him how to use them.

Solution

Fifteen automations joining the CRM to email, LinkedIn and the website, with data enrichment, lead qualification, and AI that wrote and illustrated the firm's marketing.

  • CRM records that completed themselves. Contacts went in from LinkedIn in one click, their company was created automatically, and an external data source filled in details such as job title, location, headcount and web address.
  • Qualified website enquiries. Each enquiry's company was identified from the sender's email address and checked against the ideal client, and qualified leads went into the CRM with their company details and the marketing source that brought them in.
  • Follow-ups that sent themselves. Any email the founder sent, to a prospect, candidate, supplier or colleague, could be chased automatically: if no reply came, follow-ups went out from his own mailbox.
  • AI-written, AI-illustrated content. AI turned the selling points on the firm's website into weekly branded LinkedIn carousels with AI-generated images, summarised biotech news into a weekly post for the founder, and wrote a comment for any article he chose to share.
  • Proof from every placement. After each placement, the founder filled in a short form, and AI turned it into a case study and published it on the website, and clients and candidates were asked for an online review. Positive reviews got an AI-written reply and a branded LinkedIn post.

Result

The firm gained the equivalent of more than two working weeks each month to focus on recruitment, with unanswered emails chased on time, fuller CRM records, past contacts invited back and a stronger LinkedIn presence.

  • Time back to grow the firm. Logging, research, data entry and follow-ups ran automatically, so time went on finding clients and filling roles, not admin.
  • Follow-ups on time. Unanswered emails were chased automatically, whoever they were to, so a busy day didn't leave a request or an opportunity hanging.
  • Fuller records for every conversation. Contacts were captured in one click and enriched as they were added, so he went into each conversation with clients and candidates better informed.
  • Past contacts invited back. Six personalised re-engagement campaigns, sent from the CRM, invited more than 1,200 past contacts back into conversation.
  • A stronger LinkedIn presence. Branded posts every week, and a case study and review request after each placement, kept the firm visible without taking up the founder's time.

Notes

  1. 1.Estimate: following up 40 to 50 emails a day by hand, at 5 minutes each, came to at least 60 hours a month, and six other time-saving automations added 34 more. 94 hours is more than two 40-hour weeks. ↩

Does your CRM stop short of what your team needs?

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