What a customer success leader told us about AI and keeping clients

The firms that get the most from AI use it for their clients as well as for their own hours. A client who is kept informed and sees value early tends to stay, and the clients a firm keeps are the fee income it can count on next year. Victoria Hamblin made that case from the client's side when we spoke to her last month.

Victoria is the founder of Elevate Customer Success. She has spent more than 25 years in technology and the last ten leading customer success teams in software businesses. Companies tend to bring her in when clients start to leave, renewals get harder than they should be, or a team is working flat out without seeing the results. In her words, customer success "is about protecting and growing the revenue of the customers that they already have."

AI has to improve the client's experience as well as save time

When we got onto AI, Victoria was clear about the balance. "It is about being more efficient and saving time," she said, "but it's also about improving the customer experience as well."

In a firm, the two are tied together. Plenty of teams are very good at the work and much less good at keeping the client updated while it happens. A client who hears nothing for weeks chases, and answering them, or redoing what was misunderstood, goes on the job's time. Every job has a time budget, and the fee is set from it. When a job runs over, the extra time is written off, so the firm bills less of the time it recorded and its recovery rate falls. When clients are kept informed and jobs come in inside their budget, less is written off, and the recovery rate, fee income and gross profit rise together.

Keeping clients updated is one of the new AI opportunities we look for: something a firm has never had the time to do, which AI now makes possible. A simple example is a notetaker on every client call that turns the conversation into an action plan and a first draft of the follow-up email. Even a solution that small has to be compliant and secure. Client calls carry client data, so the firm's AI policy covers the notetaker, and what it produces goes to the person who looks after that client before anything is sent.

The first weeks decide whether a client stays

The client's experience matters most at the start. Victoria thinks the biggest difference AI makes in the businesses she works with is "probably onboarding", and in particular "how you can get the customer seeing value quicker."

A firm's new client is in the same position: they have just signed, and they are waiting to see whether they made the right choice. AI makes it far quicker to give each one an onboarding that fits them, drawn from what the firm already knows about them. New clients then know from the first week what the firm needs and by when, so their first jobs are less likely to run over while someone chases what's missing.

Personalising needs complete data in one place

That only works if the information is there to draw on. Victoria told us about a company she had spoken to that day that was "still using spreadsheets for everything", and most firms have something similar, with client details split across a practice system, a few spreadsheets and several people's inboxes. AI reading from that will confidently personalise the wrong things.

So before a solution is planned, we check the layers under it: whether the firm's data is complete, kept in one place, owned by someone and secure, whether its tech stack can connect to AI, and whether its people are ready to use it. Where a layer isn't ready, fixing it goes first on the roadmap, and the onboarding solution comes after, reading from systems that hold the right information.

To see where AI would free up your own team's time first, the quiz below takes a few minutes.

Every firm will be asked what it is doing about AI

That groundwork also gives a firm an answer when someone asks about its AI. Victoria pointed to something she is seeing with companies raising investment: the big thing they are being asked now, she said, is "What are you doing for AI?" "So lots of people are trying to catch up," she told us, "and there's a lot of fear, isn't it, around it?"

For a firm, the question will come from clients, its insurer or a regulator, and some of the fear is fair, because client data is involved and the rules keep moving. A good answer covers where AI is used, what it returns, how client data stays safe and who checks the work. The data decides where each solution runs: on the AI provider's own servers when nothing sensitive is involved, on the firm's own cloud server where the provider never trains on what it sends, or on a machine in the office where the data never leaves. And as the models change, someone checks what each solution produces and tweaks it, so its quality doesn't drift without anyone noticing.

What firm leaders should do now

The company Victoria described wanted AI for a simple reason. "They just don't want to increase headcount," she said, "so that's where AI is going to be key." Most firms we speak to want the same thing, more fee income from the people they already have, and getting there follows one order, whoever does the work.

Start with the firm's own work, broken down into the individual tasks and processes that create value for its clients, including the ones clients see, from onboarding to keeping them updated.

Before any solution, check the layers those tasks sit on: the business and each department, the tech stack, the quality, completeness and security of the data, compliance and governance, and the people who will work alongside the AI. Where a layer isn't ready, fixing it comes first.

Then set out a roadmap of solutions, each fully costed with the hours it frees up, what it costs to implement, its first-year return and what it does to the recovery rate on the jobs it touches.

Implement the solutions one by one, in the roadmap's order. Each runs where its data allows, has its risks designed out, is covered by the AI policy and has a named owner who checks what it produces before it reaches a client. Once they are live, keep managing them as the models change, with the firm owning its knowledge and renting the AI.

Done in that order, the firm keeps its clients better informed, gets more capacity from the same team, hits its chargeable time targets and lifts its recovery rate and fee income, in a way that is compliant and keeps client data secure.

See where your firm stands

Our quiz asks how much of your team's week goes on repeat work, how often jobs run over budget, how your team uses AI, where client data goes and how you would know whether AI paid off. Your report shows where AI would free up your team's time first, the capacity it could give your firm in hours, and a 30-day plan for what to do.

If you want our support putting it in place, book a free call.