Kvell Digital

Kvell Digital We assist companies in generating customers by implementing our specialist marketing and sales strategy.

We specialise in providing businesses and companies with professional practices with a practical, measurable online marketing strategy and solutions.

That probably sounds strange coming from someone who spends a considerable amount of time thinking about how businesses ...
11/09/2026

That probably sounds strange coming from someone who spends a considerable amount of time thinking about how businesses can use AI.

But I keep hearing variations of the same concern.

“We need an AI strategy.”

My first question would be: for what?

If the answer is that competitors are using AI, the board is asking about it or everyone seems to be talking about agents, I'm not convinced we're ready to discuss strategy yet.

A strategy needs an objective.

Perhaps the business needs to reduce the amount of administration around sales. Maybe customer enquiries are taking too long to handle. Perhaps management has a large amount of information but struggles to turn it into something useful. There may be knowledge sitting across documents, systems and people's inboxes that employees waste hours trying to find.

Now we have somewhere to start.

I'd be much more comfortable with a business identifying three meaningful problems and using AI well against one of them than producing a twenty-page AI strategy containing twelve initiatives nobody has the capacity to implement.

There is also a tendency to assume AI should sit in its own category. I'm not sure that's going to make sense for very long.

We don't normally have an “internet strategy” anymore. The internet simply became part of how sales, marketing, finance, operations and customer service work.

I suspect AI will move in the same direction.

For now, some strategic thinking is obviously necessary, particularly around data, governance, security and where human judgement remains important. But I wouldn't confuse having those principles with needing to find AI projects everywhere.

💡 A business doesn't need to prove that it is using AI. It needs to prove that the AI it uses is improving something worth improving.

That's the strategy I'd rather see.

There’s a particular kind of meeting I’ve been in many times over the years. Everyone is around the table, the presentat...
10/09/2026

There’s a particular kind of meeting I’ve been in many times over the years. Everyone is around the table, the presentation is good, the numbers make sense and there seems to be general agreement about what happens next. You leave thinking the decision has been made.

Then the interesting conversations begin.

Someone catches you afterwards and asks, “Do you think this is actually going to work?” Another person wants to know what happens if the assumptions are wrong. Someone else quietly mentions that the team has tried something similar before and it didn't go particularly well.

I've come to pay a lot of attention to those conversations because they often contain information that never made it into the meeting.

It's not necessarily because people are being political or withholding information. Formal meetings create their own dynamics. There is an agenda, limited time and usually some pressure to reach a conclusion. Once the room appears to be moving in one direction, challenging the underlying assumption can become harder.

I've seen this in technology projects, sales discussions and broader business decisions. A plan can look very convincing at the level of the presentation while the people closest to the work already know where the difficult parts are likely to be.

These days, when a decision seems to attract agreement very quickly, I'm inclined to ask a few more questions. What are we assuming has to be true for this to work? What are we not particularly confident about? If this fails six months from now, what will we probably say we should have noticed?

I'm not trying to make decisions slower. Quite the opposite.

I'd rather spend another twenty minutes finding the uncomfortable part now than six months discovering that everyone knew about it but nobody thought it was the right moment to say something.

Sometimes the most useful information in a meeting is the thing someone was going to tell you afterwards.

There is a stage in building almost any business where heroics are unavoidable.A major customer has a problem and somebo...
07/09/2026

There is a stage in building almost any business where heroics are unavoidable.

A major customer has a problem and somebody stays late to sort it out. A deal is about to fall over and the owner steps in. Something goes wrong with a process and the person who understands it finds a workaround before anyone else even knows there's a problem.

Those moments matter.

They build trust, save customers and sometimes keep the business moving through genuinely difficult periods.

The problem is when exceptional behaviour becomes an ordinary requirement.

If the owner needs to become involved every time an important customer complains, I don't think that's simply evidence of an engaged owner.

I'd want to know why nobody else can resolve it.

If month-end repeatedly works because someone in finance spends two days repairing information manually, I'd want to understand why the repair has become part of month-end.

If revenue targets are achieved because one salesperson repeatedly produces half of the company's new business, I'd be grateful to have that person.

I'd also be asking what happens if they leave.

This is one of the distinctions I think becomes important as a business grows:
▪️Heroics are useful when something unusual happens.
▪️They become dangerous when ordinary operations depend on them.

There is a temptation to celebrate the people who continually rescue the business, and they certainly deserve recognition.
But leadership also needs to pay attention to what they're repeatedly rescuing it from.

Maybe the process isn't good enough.
Maybe the information isn't available.
Maybe decision-making sits too high in the organisation.
Maybe responsibility has never been made clear.

A mature business doesn't remove the need for talented, committed people.

It gives those people better problems to solve.

If your best people spend their time rescuing the same ordinary process every week, that's not really making the best use of them.

At some point, the business needs to fix what they're being heroic about.

One of the stranger consequences of sales automation is that we've become very good at not leaving people alone.Didn't r...
04/09/2026

One of the stranger consequences of sales automation is that we've become very good at not leaving people alone.

Didn't reply to the email?
Send another.
Still nothing?

LinkedIn message.
Wait three days.
Another email.
Perhaps refer to the email they didn't answer before.

By the time the sequence finishes, we've “touched” the prospect twelve times.

The metric looks impressive.

I'm less certain about the experience.

There are good reasons for following up in B2B. Buying cycles are long, people's priorities change and a relevant conversation shouldn't disappear simply because somebody was busy when the first email arrived.

But I think we need to distinguish between persistent follow-up and useful follow-up.

Before sending another message, I'd ask:
▪️Do I have something new to say?
▪️Have I learned anything useful about their business?
▪️Has something changed that makes this relevant now?
▪️Can I help with a problem they've actually indicated they have?
▪️Would I send this message if the automation wasn't reminding me?

That last question is quite revealing.

If the only reason for contacting someone today is that the workflow says Day 11: Follow-up #4, perhaps another touchpoint isn't what the relationship needs.

Technology has made attention cheap for the sender.

It hasn't made attention cheap for the recipient.

That's an important difference.

The better sales automation becomes, the more valuable I think judgement will become alongside it.

Knowing when to follow up matters.

Knowing when not to is part of sales too.

Every established business has people who know how things really work.They're incredibly valuable.They know that a parti...
03/09/2026

Every established business has people who know how things really work.

They're incredibly valuable.

They know that a particular customer prefers a phone call before anything gets changed. They know one field in the CRM shouldn't be trusted until another report has been checked. They know which person in finance can fix something when the normal process gets stuck.

The organisation often doesn't realise how much knowledge sits with these people until they're unavailable.

Then you start hearing questions such as:
❓ “How does Sarah normally do this?”
❓ “Where does John get that number?”
❓ “Who approves this when Michelle isn't here?”
❓ “Does anyone know what we normally tell this customer?”

That's usually the point where institutional knowledge becomes visible.

I'm not suggesting businesses should respond by documenting every tiny action and creating another hundred-page procedure manual. That can become just as unhelpful.

But there is a sensible middle ground.

If a piece of knowledge affects customers, revenue, cash flow, compliance or another person's ability to complete their work, I'd want it to exist somewhere other than one person's memory.

Good people should make a process better.

They shouldn't be the only reason the process works.

A useful test is surprisingly simple.

Could this continue reasonably well if the person who normally handles it took three weeks off tomorrow?

If the answer is no, you may have found a dependency worth addressing.

Not because the person isn't valuable.

Because they are.

When I was younger in my technology career, I was naturally fascinated by the systems themselves. What could the softwar...
01/09/2026

When I was younger in my technology career, I was naturally fascinated by the systems themselves. What could the software do? How could we integrate it? Could the process be automated? What would the new platform enable that the old one couldn't?

I still enjoy that side of technology. You don't spend years around ERP, CRM, automation and business systems without retaining an interest in how things work.

What has changed is where I start.

These days, I'm far more interested in questions such as why finance doesn't trust a report that supposedly comes from the source system, why salespeople have developed a parallel process outside the CRM, or why management has more dashboards than ever but still struggles to work out what's actually going on.

I've also become wary of technically elegant solutions that create operational complexity.

I've seen systems capable of doing extraordinary things that people barely use.

I've seen businesses pay for capabilities they already had because nobody realised the existing platform could do them.

And I've seen relatively unsophisticated solutions work very well because they fitted the business, people understood them and everyone trusted the information.

That experience changes how you think about AI too.

I'm interested in what AI can do, but I don't think “using AI” is a meaningful business outcome.

If it reduces the administrative burden on a salesperson, that's interesting.
If it gives management information earlier enough to make a different decision, that's interesting.
If it helps a business respond to customers better, that's interesting.
If we're introducing it mainly because everyone else seems to have an AI initiative, I'm considerably less excited.

After enough years around technology, I think you become less interested in whether something is technically impressive.

You start asking whether it makes the business noticeably better.

That's a much harder standard.

Probably a more useful one too.

A workaround doesn't normally begin as a bad decision.Quite often, it's actually a clever response to a problem.Someone ...
31/08/2026

A workaround doesn't normally begin as a bad decision.
Quite often, it's actually a clever response to a problem.

Someone discovers that the CRM can't easily show what they need, so they build a small spreadsheet. Someone in finance finds that copying information manually is quicker than changing the system. A salesperson keeps a few notes outside the CRM because they know exactly where to find them.

When five people are running the business, those things can work perfectly well.

The difficulty comes later.

The company grows. New people join. The workaround gets passed on as part of the job. Then somebody adds another column to the spreadsheet, another manual check to the process or another step to compensate for something that went wrong once.

Nobody sits down one morning and deliberately creates a complicated operating model.

It accumulates.

That's why I think some operational problems are actually growth problems in disguise.

At 10 people, the workaround was sensible.
At 30 people, it's becoming inefficient.
At 100 people, you're paying dozens of people to compensate for something that should probably have been redesigned two years earlier.

There are a few signals I'd pay attention to in a growing business:
▪️The same information is being maintained in more than one place.
▪️New employees need to learn “the real way” as well as the documented way.
▪️Managers are checking things manually because they don't trust the system.
▪️People are spending increasing amounts of time reconciling information.
▪️A process stops when one particular person is unavailable.

None of these automatically means you need new technology.

But they are useful signs that something designed for a smaller business may be reaching its limit.

Growth doesn't only increase revenue and headcount.

It puts pressure on all the little informal arrangements that made the earlier version of the company work.

I've seen marketing campaigns written off surprisingly quickly.“The leads weren't good.”“The targeting is wrong.”“We nee...
31/08/2026

I've seen marketing campaigns written off surprisingly quickly.

“The leads weren't good.”
“The targeting is wrong.”
“We need a different message.”
“We need more decision-makers.”

Sometimes that's exactly the problem.

But before rebuilding the campaign, I'd take ten or twenty recent leads and follow them manually from the moment they entered the business.

Not just through the reporting dashboard.

I'd actually look at them.
🔎 When did the enquiry arrive?
🔎 When did the first meaningful response happen?
🔎 Did somebody genuinely try to understand what the prospect needed?
🔎 If they couldn't reach the prospect, what happened next?
🔎 Was another useful follow-up made, or did an automated sequence simply continue?
🔎 If the opportunity was eventually marked as lost, do we know why?

That exercise can be uncomfortable because it moves the conversation away from averages.

A dashboard might say the business generated 80 leads.

Looking at individual leads might reveal that nine waited more than two days for a response, six received one email and nothing further, four were assigned to the wrong person and several are still sitting in the CRM with no meaningful status.

Now the marketing conversation looks quite different.

There's a reason I like following the actual customer rather than only examining aggregate data.

A poor campaign and a poor follow-up process can produce very similar results.

The solution, however, is completely different.

A business can do an excellent job of generating interest and still conclude that its marketing isn't working.I've seen ...
28/08/2026

A business can do an excellent job of generating interest and still conclude that its marketing isn't working.

I've seen this become particularly confusing in B2B because the marketing metrics often look perfectly respectable. The right people are seeing the content. Website traffic is increasing. Prospects are engaging. Enquiries are arriving.

Then the commercial outcome doesn't follow.

The natural response is to go back to marketing.

Change the campaign.
Change the message.
Find another audience.
Spend more.

Before doing that, I'd want to look at what happens immediately after someone becomes interested.

A prospect fills in a form on Monday morning. What happens next?
Do they hear from somebody that afternoon or on Thursday?
Does the person calling them know which service they were looking at?
Can they see what the prospect downloaded, read or asked about?
Does the conversation pick up naturally from the marketing experience, or does the prospect effectively start again?

This is where the organisational structure can get in the way of seeing the customer experience properly.

Inside the business, we might see:
Marketing → Lead → Sales → Proposal → Customer

The prospect doesn't see any of that.

For them, there is just one company.

They don't care that the website belongs to marketing and the phone call belongs to sales. They don't care that an enquiry moved from one system into another or that responsibility changed departments somewhere along the way.

They simply know whether dealing with the company felt easy.

That's why I think marketing performance should sometimes be examined much further downstream than the marketing dashboard.
Marketing can create attention and interest.

It can put a genuine opportunity in front of the business.

But once someone raises their hand, the rest of the organisation has to justify the marketing investment.

I'm all for reducing waste in a business. If a process takes five hours and it can reliably be completed in one, there's...
26/08/2026

I'm all for reducing waste in a business. If a process takes five hours and it can reliably be completed in one, there's an obvious reason to improve it.

What interests me more now is what happens to the four hours we just saved.

AI and automation are making this question increasingly important because we can suddenly make large amounts of work faster.

But there are two very different versions of efficiency.
⚙️ Version one: We remove unnecessary administration so people have more time to do valuable work.
⚙️ Version two: We remove unnecessary administration and immediately replace it with a larger volume of activity.
I'm much more interested in the first.

If AI gives a salesperson five hours back and those hours are spent having better conversations with customers, understanding accounts more deeply or following up genuine opportunities properly, there is a clear business benefit.

If those five hours are used to send another 2,000 automated messages, we've certainly increased output.

I'm not sure we've increased value.

The content world is another good example. We can now produce ten times as much content for a fraction of the effort. That's technically an efficiency gain. But if the result is ten times as much material that people don't particularly want to read, we've simply become more efficient at creating something nobody needed.

I think this is where business leaders need to be careful with the productivity conversation around AI.

The objective shouldn't automatically be more output per person.

Sometimes the better outcome is more thinking time, better customer conversations, fewer mistakes, faster access to information or simply less pointless work.

Efficiency matters.

But I'd still want to know what we're becoming efficient for.

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