Podcast

Why Chasing Revenue Can Make You a “Busy Fool”

By Pricemaster Team
October 12, 2026

Reid Archer joins the Leaders on Shopify Podcast to talk ecommerce, pricing, profit, Google Ads and the future of AI shopping

Pricemaster Co-Founder Reid Archer recently joined the Leaders on Shopify Podcast for a wide-ranging conversation about what nearly two decades in ecommerce has taught him about pricing, margin, advertising and profitable growth.

The episode, “Why chasing revenue can make you a ‘busy fool’, and why Google will never tell you to spend less”, follows Reid’s journey from selling products on eBay to operating eight ecommerce stores, moving a 175,000-product catalogue onto Shopify and ultimately building Pricemaster to solve problems the business was experiencing itself.

But the central theme is simple:

Revenue is important. Profit matters more.

For the shorter announcement and direct listening links, see Reid Archer joins the Leaders on Shopify Podcast.

18 years of ecommerce experience

Reid has worked in ecommerce for around 18 years.

His journey began selling products through eBay before developing Trade Counter Direct, an online retailer specialising in power tools, hand tools, plumbing tools and other products for the trade.

Over time, the business expanded into a collection of specialist ecommerce stores covering areas including workwear, power tools, building products and tool storage.

Today, the group operates eight ecommerce stores on Shopify.

As those businesses grew, however, the complexity grew with them.

At one point the team was managing more than 100,000 different SKUs, with supplier costs, competitor prices, stock availability, advertising costs and selling prices constantly changing.

Managing that manually became increasingly unrealistic.

And that is ultimately where Pricemaster started.

Pricemaster was built to solve our own problem

One of the first problems was straightforward.

Supplier costs would change, but those changes weren't always making their way through to the selling price quickly enough.

A cost could increase while the retail price remained unchanged.

The product might continue selling well, but every sale could quietly be reducing the margin.

So one of the first safeguards built into Pricemaster was Minimum Margin protection.

But supplier costs were only one moving part.

Competitor prices were changing constantly too.

On Trade Counter Direct alone, the team can see around 7,000–8,000 market price changes in a seven-day period.

When you're dealing with thousands of products, it simply isn't possible for a person to review every change and decide:

Should we go down?

Should we stay where we are?

Can we put the price up?

Are we already too cheap?

Is this product even sensitive to competitor pricing?

Those questions pushed Pricemaster beyond basic competitor monitoring and towards what it is today: a platform designed to help ecommerce businesses make better pricing, margin and profitability decisions at scale.

Automated pricing shouldn't mean a race to the bottom

Traditional repricing has often been built around one basic idea:

Be cheaper than the competition.

A competitor drops by 1p.

You drop by 1p.

They respond.

You respond again.

Eventually everyone has automated themselves towards the lowest possible price.

We wanted Pricemaster to approach the problem differently.

Instead of constantly asking:

“How can we become cheaper?”

We want retailers to be able to ask:

“Where can we make more margin without damaging sales?”

Sometimes being the cheapest or one of the cheapest sellers in the market is important.

But not every product behaves the same way.

Some products may sell just as well at a higher price.

Some may have very little price sensitivity.

Others may require a highly competitive market position.

Understanding that difference is where better pricing decisions start.

Don't guess the right price. Test it.

One of the areas discussed on the podcast is price discovery.

Imagine a product is consistently selling 20 units per day.

Instead of assuming its current selling price is the optimum price, you could test a small increase.

If sales remain stable, the new price can be validated.

Then another controlled test can be made.

Over time you begin building a picture of the relationship between:

Price. Sales volume. Margin. Profit.

That data can start answering much more useful questions.

Where is the best price for maximum volume?

Where is the best price for stable profit?

How much can the price increase before demand materially changes?

That is much more valuable than simply looking at a competitor and copying their price.

The objective is to build your own pricing intelligence from your own customers and your own sales data.

AI should support the strategy, not become the strategy

AI naturally came up during the podcast.

Our view is that ecommerce businesses shouldn't simply hand complete control of their pricing over to an AI model.

Pricemaster's pricing engine is deliberately built around controlled rules and safeguards.

The retailer remains in control of things such as:

Minimum margins
Competitor strategies
Market positions
Product groups
Sales rules
Pricing tests
Pricing thresholds

AI can then sit across that information and help identify opportunities.

It might highlight fast-moving products that could justify a different strategy.

It might identify slow-moving stock.

It could highlight products where your market position looks wrong.

Or it could help identify areas where a different pricing rule may be worth testing.

The aim is to combine automation, AI and human commercial judgement, rather than simply handing the keys to a black box.

Price isn't only about your competitors

Another important part of pricing is stock.

If a competitor is out of stock, should you really price-match them?

Probably not.

Likewise, imagine you have a product selling extremely quickly but you only have a small amount of stock remaining.

Reducing the price to generate even more demand may be completely unnecessary.

You might actually want to increase the price, protect the remaining stock and maintain availability until the next delivery arrives.

Then the situation changes again when a large quantity of new stock lands and you want to increase sell-through.

That is where we see pricing becoming increasingly connected with the wider commercial picture.

Over time, pricing decisions can potentially take into account:

Current stock
Incoming stock
Sales velocity
Supplier costs
Minimum margin
Competitor prices
Competitor availability
Market position
Advertising spend

Because ultimately, a competitor's selling price is only one data point.

The real question is:

Is this sale worth making at this price?

Revenue isn't profit

One of the biggest themes in the conversation is the danger of becoming a “busy fool.”

Ecommerce businesses naturally focus on growth.

£5 million revenue.

£10 million.

£20 million.

And growing revenue can feel like success.

But revenue alone tells you very little about the quality of that growth.

As Reid explains during the podcast, there isn't much point doing £20 million in sales if you're not making enough money at the end of it.

More sales can mean more:

Advertising
Fulfilment
Warehousing
Staff
Stock
Working capital
Returns
Operational complexity

It is entirely possible to build a much bigger business without building a more profitable one.

That's why we believe ecommerce businesses need to look beyond top-line sales and understand the real margin behind the activity generating them.

Google is unlikely to tell you to spend less

That leads naturally into another major topic from the conversation: Google Ads.

Google is incredibly important to ecommerce.

But Google is also a commercial business.

Its business model benefits when advertisers spend money.

An ecommerce retailer, on the other hand, wants to generate the greatest possible profit from that spend.

Those aren't necessarily the same objective.

As discussed on the podcast, you probably shouldn't expect Google to sit in a meeting and say:

“You'd be better off spending less money with us.”

That isn't an attack on Google.

It's simply why ecommerce businesses need their own commercial data and controls around advertising.

ROAS can be useful.

But ROAS doesn't tell you everything.

A business advertising thousands of products could have completely different margins, stock positions and competitive positions across every SKU.

Two products could report exactly the same ROAS while generating completely different levels of actual profit.

Why advertise a product when ten competitors are cheaper?

This is where we think market pricing data and advertising data become particularly powerful together.

Imagine Pricemaster can see that you're currently the cheapest credible seller of a product.

Your price is competitive.

Your stock is available.

Your margin is healthy.

That's potentially a very good product to support with advertising.

Now consider the opposite.

You're currently 10th cheapest in the market and several established retailers are selling the identical product below you.

Should you continue spending heavily to send traffic to that SKU?

Maybe not.

You could simply be paying Google to send shoppers to a product page that isn't competitively positioned enough to convert.

That is why one of the areas we're increasingly interested in is bringing advertising data and pricing intelligence together.

Not simply asking:

“How much revenue did our ads generate?”

But:

“Which products is it commercially sensible to advertise in the first place?”

Reducing wasted spend can be just as valuable as increasing sales.

Moving 175,000 products from Magento to Shopify

The podcast also covers Reid's journey through different ecommerce platforms.

Trade Counter Direct originally operated on a custom-built PHP ecommerce platform before later moving to Magento.

Magento played an important role in helping the business grow, but running a large catalogue became increasingly demanding.

Meanwhile, the group's smaller specialist websites were being built on Shopify.

Eventually, the decision was made to move the main business across as well.

It wasn't a small migration.

Around 175,000 products were moved from Magento to Shopify in approximately three to four weeks.

Pricemaster played an important part in making that possible.

Much of the underlying product information, categorisation and enriched data had already been brought together within Pricemaster, effectively giving the team a structured data source to help move the catalogue into Shopify.

Today, all eight stores operate on Shopify.

Why we still run ecommerce stores

There's also an important reason why Pricemaster and our ecommerce businesses continue to coexist.

Our stores are where we test our ideas.

When we develop a new pricing concept or commercial strategy, we can test it using real businesses, real products, real customers and real money.

Sometimes those tests work.

Sometimes they don't.

But when something proves genuinely useful, we can take what we've learned and build it into Pricemaster.

That connection matters.

Because the moment you completely step away from operating ecommerce businesses, it becomes much harder to understand the problems ecommerce businesses are actually facing.

Pricemaster wasn't created from a theoretical idea of how ecommerce pricing should work.

It came from trying to solve our own problems.

And we want to keep it that way.

What happens when AI starts doing the shopping?

The conversation also looks further into the future.

AI shopping agents could fundamentally change the way people buy online.

Instead of a customer manually searching multiple websites, comparing prices and waiting for an offer, an AI agent could potentially monitor products continuously and act when the customer's buying conditions are met.

That creates some fascinating questions for ecommerce pricing.

Imagine thousands of AI agents are watching the price of a product.

What happens if reducing the price by £1 suddenly triggers hundreds of purchases?

Could retailers eventually test those thresholds?

Could pricing systems begin to understand the price points that cause automated shopping agents to act?

And could ecommerce businesses find themselves monitoring the agents that are monitoring them?

We're still at the beginning of that shift.

But as AI plays a bigger role in product discovery and purchasing, understanding price elasticity and market behaviour could become more important than ever.

Listen to the full Leaders on Shopify Podcast

The full conversation covers Reid's ecommerce journey, the origins of Pricemaster, Shopify, Magento, pricing automation, stock, Google Ads, AI and where ecommerce may be heading next.

Want to understand what's really happening around your prices?

Pricemaster brings together competitor pricing, market data and your own commercial information to help ecommerce businesses protect margin, automate pricing strategies and identify opportunities to improve profitability.

Pricemaster works with Shopify, WooCommerce, Magento and Linnworks-connected businesses, alongside other ecommerce integrations.

If you'd like to see what Pricemaster can identify across your products and competitors, book a demo or speak to the team.