Goodbye waste, hello profit: Why retail’s advertising problem is really a data problem

The unacceptable truth of online retailing

It’s no secret that right now is a difficult time for the retail industry. The majority of retail businesses are already working to unacceptable margins dealing with a profit gap that sees an average 60% gross margin fall to around 5% Net. And after the COVID-19 pandemic’s online shopping boom and post-lockdown splurging that saw many businesses receive significant sales boosts, a rapidly worsening economy has brought things firmly back down to Earth.

In mid-November, the UK’s inflation rate topped 11%, driven by global supply chain issues, the lingering effects of COVID-19, and ongoing conflict in Ukraine. Inflation’s consequences for businesses range from low customer confidence and reduced sales to difficulties getting the stock and materials they need. And retailers can be especially vulnerable to these challenges if they’re not providing a product or service that’s seen as absolutely essential to people’s daily lives. 

In a market like this, it’s more important than ever to cut through the noise and reach customers with relevant, tailored messaging that ultimately leads to sales. But growth at any cost is no longer an option. And the return on many retailers’ digital advertising spend (ROAS) simply doesn’t make good business sense. Performance Marketing is currently seen as a cost by retailers and a large part of the unmanageable profit gap. Why? In a harsh environment of increasing costs, increased competition, and fewer customers performance marketing costs are high, and PPC and marketing teams don’t have enough visibility or control of their marketing channels to take make effective profitable sales. And any performance marketing channel – from SEM (search engine marketing) or social media – Google, Meta or Amazon, will eat away at any potential profits if their platforms and processes aren’t used in the most effective ways. 

The trouble with online advertising

A lot of retailers have high revenues. The problem is that through a variety of factors, shown in the funnel above, their overall profit is chipped away until it falls lower and lower. Advertising is one of the most valuable tools that businesses have to turn their profits around. But when it comes to digital marketing, the associated costs can quickly spiral out of control, taking up a significant chunk of annual budgets.

In 2021, retail accounted for nearly a quarter of all digital ad spending in the US, growing by 34.5% compared to the previous year. The trend is clear – retail businesses are doing what they’ve always done and turning to digital marketing to reach and convince an audience to spend.

On this side of the pond, online shopping is more popular in the UK than in any other country in the world, and it’s still growing fast. In 2022, eCommerce accounts for roughly 30% of the total UK retail market, but the important detail is that this figure has increased from 20% just two years earlier in 2020. And the result of this shift in behavior is intense competition. With easy comparisons between prices and products just a few clicks away, advertising remains crucial for retailers that want to stay front and centre in customers’ minds.  

Google, is by far the largest Global marketing channel, and despite the economic climate, Google’s ad revenues continue to climb. In 2021, the company’s overall annual revenue increased by 41.2% to $257.64 billion, representing the highest rate of growth for the tech giant since 2007. That’s no surprise. And retail’s share of advertising spending on Google is by far the largest across all industries – increasing faster than any other sector, with growth of over 20% in 2022. And whilst retailers are suffering, Google’s advertising business isn’t, with retail spending boosting its ad revenues by 32.6% year-over-year to $61.24 billion in Q4 2021. 

But with businesses having to account for every penny spent in today’s economic environment, continuing to pour money into digital ads and hoping for future returns just isn’t sustainable. Instead, retailers need to know that they’ll get the right return on any marketing investment – improving margins by making the absolute most of Google as a sales channel. 

The question is, how? 

Data holds the key to increased profitability for online retail

The problem is, as much as 40% of digital advertising spend generates £0 in real-world sales. And that’s before taking into account the costs of getting campaigns going in the first place. 

There are two ways that retailers run their advertising. The first is with an in-house team, of eCommerce experts, PPC and Advertising managers, and data scientists, who need to be hired, trained and supported with the budget to launch digital adverts. The alternative is to engage an advertising agency, which can outsource the need for a team and often bring deeper ‘best practice’ strategies – along with challenges in ensuring that the agency understands its client’s structure, strategies, and market positioning. And, these agencies have even less access to essential business operations data than a retailer’s in-house team.

However, both of these traditional methods fall down in the same two areas:
1) There are limits to how much visibility either team has of the data they need, because the abundance of valuable data that’s the key to transforming eCommerce is sitting in silos. Held in a plethora of in-house reporting suites, and unsuitable to be managed by an agency.

2) The diversity of the data and the speed with which relevant changes happen, would make it impossible for even the largest data science team or top ad agency in the world to digest at the speed necessary to keep up with the changes in online auction dynamics.

So in either case, the likely outcome is the same: high investment – with little control, visibility, or ROI. If you ask any retail CFO or CMO, this is the common thread in the issues they are facing – which makes it impossible for them to align, as budgets are difficult to justify because marketing channels are inconsistent at best and unprofitable at worst.
However, the problem here isn’t the marketing channel itself, which is doing the best job possible with the data and parameters it has. The problem is that no one is able to leverage the advantage that all retailers have – their own data, to connect the dots between supply and demand and implement changes at the speed required for effective online retailing.

Critical data that retailers are ignoring

With Google’s platforms – like any machine-learning technology – it really is true that you get out what you put in. The more data you can feed into Google, the more it will have to learn from. However, even with accurate data Google’s remit is to provide ROAS. So Google quickly tests your inventory, accurately determines which of your products will sell the best to provide this return and then concentrates all of its efforts on these products,

There is currently nothing in place to ensure what is truly necessary for retailers – an intelligent ROAS based on a retailer’s goal around either profitability or generating revenue. For this, not only does the data given to Google need to be richer, Google needs to ‘do’ something with it. And even with the advancements of Performance Max, this is not set up (and ultimately, let’s face it, not possible because the data needs to include a retailer’s first-party data). With Google, when a retailer provides the right information, such as applying promotions, there is currently very little in place to ensure that this information is acted upon to ensure the right ads will be served to the right people in the right place at the right time.

So where can you find information that has that accuracy? When it comes to retail, there are four key data silos to keep in mind:

• Advertising: No industry spends more on advertising than retail, and there’s a lot more to it than overall budget or ROAS. To get a full picture, it’s important to look at auction, individual product, and ad asset data.
• Business operations: Anything and everything that can be collected about a business and its products falls into this category. From price points and stock availability all the way through to return rates, order information, and even the costs associated with producing each product in the first place (COGs).
• Customer decision influencers: Customer data is always highly prized, but it goes so much further than basic demographic and geographic information. Incorporating delivery details, recent reviews, and the effects of promotions on customer behavior are all critical – helping to shape an accurate picture.
• External trends: Last but not least, no purchase happens in a vacuum. Factors like seasonality, competitor activity, and web traffic can all have huge impacts on retail, so it’s imperative to stay on top of them. 

Retailers have all the above information and spend a great deal analyzing it. However, currently retailers have no way of connecting and analysing their data – let alone doing it in real-time as online auctions demand. And they therefore lack the critical visibility that empowers better decisions.

Retailers work hard to ensure they have a robust data strategy in place, but currently it’s impossible for that strategy to be acted on across the entire organization which is why less than a third of US retailers reporting that strategy is clear and widely understood across the business.

Flipping the model with Upp.

Upp.® connects the data with a retail intelligence ecosystem that is transforming Google Shopping by ensuring retailers sell both more effectively and more profitably. At its core, Upp connects previously disparate data sets to form a unique decision-making system for each and every SKU advertised on Google – automating advertising decisions at unrivaled speed and scale, to drive better ROI, better outcomes and reduce wasted advertising spend. 

With inventory at its heart, Upp currently optimizes more than 85 million SKUs. And every single one has over 120 unique data points that are being managed and updated 24/7 – every single day of the year. That’s 7 billion analyses per day – which is simply impossible for any human team. 

Upp. scales Google Shopping at a pace that is impossible without the technology, and works in a much more intuitive way than is currently possible with traditional methods.
INTELLIGENT ROAS replaces ROAS as Upp’s artificial intelligence works with individual SKUs to quickly group them into the most optimal Google Shopping campaigns and then works out the correct ROAS budget for each individual SKU. And this is constantly checked, tested and optimized by Upp’s unrivaled ML. Upp. is even able to establish the true break-even point for every single product in your inventory, and can combine this with the necessary contribution margin to establish the iROAS™ needed for profitable, sustainable sales on Google Shopping.

With Upp. there is no need for agencies and marketing teams to work ‘in the dark’ and crucial advertising decisions, are made the instant it’s required. Google Shopping campaigns are built using all of the intelligence available, instead of ‘best practice’ and then continually optimized with powerful ML.

Looking at the diagram below, you can see that by considering all of this data the right advertising decisions are made in real-time capitalizing on demand and reducing wasted ad spend. 

Retail future with iROAS

By establishing an intelligent ROAS (iROAS™), if you know that some of your products is selling reliably well, you won’t need to worry about discounting it to try and get customer attention, or you can choose to put more of your advertising spend behind it, to reach a wider audience.  

Gone are the days when retailers had to simply ‘set and forget’ their online advertising. And with costly 90 day retrospectives a thing of the past, so is the common issue of wasted spend on ads for a product that’s either out of stock or out of date. With the right inventory data being continuously fed into marketing decisions, that’s an easy situation to avoid. 

And by understanding the true break-even point for each product at the point of sale, you can also begin to look at the other key levers in eCommerce promotions, pricing and delivery with a new lens.

A good way to consider the benefits of using extra data is to reflect on what your decisions are based on without it. If you’re only using the standard consumer information that Google already has access to, then you have no advantage over any of the countless other online retailers running the exact same types of campaigns. 

Plus, inventory and operational data are likely to be the most accurate information a business collects. So by leveraging business-specific details that you already have access to – and that nobody else ever will – you’re essentially creating your own bespoke advertising platform. One that puts more in to get more out, and then passes its decisions along to Google’s platform in the form of thousands of micro-optimisations. Each based on up-to-the-minute data, and ensuring that advertising spend is directed to wherever it will have the most impact. 

In essence, think of Upp. as an operating system for eCommerce. One that uses real-time, data-driven decisions to achieve commercial goals, and gives retailers the freedom and time to focus on other areas of their business.

Reframing advertising around business goals

To get to a place where businesses are seeing the right results from their advertising spend, it can be helpful to shift away from the traditional ‘return on ad spend’ or ROAS model towards something more precise. This is becoming known as ‘profitable return on ad spend’ (often abbreviated to PROAS or POAS), and it provides a far more useful perspective of how campaigns are performing in relation to commercial objectives. 

With ROAS, you’re measuring the amount of money earned back for every pound spent on advertising. Theoretically, if the amount earned is higher than the amount spent, then you’re running a profitable campaign. But the problem is that ROAS typically doesn’t take into account other outgoings – which could include shipping, payment processing fees, and a host of other fixed costs that all eat away at overall profit. When you look at it this way, it’d be more accurate to describe ROAS as revenue on advertising spend, rather than true return. 

ROAS has been the industry standard for a long time. But as campaigns and advertisers have grown in sophistication, it’s possible to focus specifically on the profit – and that’s where PROAS comes into play. By incorporating additional layers of data – from the price of purchasing or manufacturing a product through to any costs after a sale is made – it provides an incredibly valuable metric that shows the full financial picture. And that’s important, because it allows businesses to prioritise campaigns that benefit their bottom lines, instead of being stuck in a cycle of ads that seem to be performing well, but aren’t leading to as much profit.

In some cases, ROAS and PROAS can paint very different pictures of a campaign’s success. For example, if you sell five units of two different products – one for £5,000 and the other for £2,000, each with an advertising spend of £2,500 – then ROAS will give you a figure of 1,000% (10:1) and 400% (4:1) respectively. 

That, and the prices of each product, would seem to indicate that the first one is the better performer. But if that first product came with £4,000 in associated costs per unit, and the second just £100, the PROAS comes to a much lower 200% (2:1) for the more expensive product, compared to 380% (3.8:1) for the cheaper one.  

Put in the most basic terms, the net profit on the more expensive product would work out to £2,500, while the cheaper one brings in a total of £7,000. 

This is obviously a simplified example, but it underlines the value of incorporating data into decisions. By focusing advertising around products with the highest PROAS values, businesses are that much more likely to see an overall profit on their advertising spend.

However, even PROAS does not go far enough – with Upp. retailers gain the ability to decide if their return on ad spend is based on profitability or ensuring a certain revenue target – intelligent ROAS is finally possible (iROAS)…

Time isn’t on your side, but technology is

Data-driven advertising decisions and the shift from a ROAS approach to iROAS make sense, but they aren’t things that digital marketing agencies or PPC teams can start doing without technology.

The volume of information needed to get things going in the right direction is huge. Even if a business were to try to implement similar processes in-house or with an agency, the time and money required would be enormous. And neither are luxuries that retailers can afford. 

Right now is an incredibly turbulent time for businesses – underlined by the recent collapses of Eve Sleep, Made.com, and Joules. The cost of living crisis in the UK and around the world is leaving customers with less money to spend, and pressures on retail are only increasing.

With Upp. retailers really can “do more with less” as the total costs of operating with Upp are actually lower.
Within 24 hours, Upp can begin to actively improve a retailers Google Shopping channel, transforming it into a profitable, certain revenue stream. Within 90 days, the average results speak for themselves: 

• +48% increase in available budget spent 
• +151% increase in overall revenue growth
• +62% increase in rate of transactions
• +16% increase in purchases from new customers

By keeping a 360-degree perspective on each and every SKU and all of the data associated with them, Upp. helps retailers make the most of demand when it’s there, avoid waste when it’s not, and optimize advertising spend to increase overall profitability. 

How online retailers achieve commercial success with Upp.

The best way to see the impact that Upp. has on a business’s bottom line is to look at some of the results customers have already achieved. From fashion to homeware and from health to lifestyle, it’s a platform that works for retailers of every shape and size. 

Charles Tyrwhitt has been around since 1986. Since then, the business has seen many different waves of customer behavior come and go. But what’s remained constant is its commitment to high quality and unbeatable value – characteristics that are more important than ever when times are tough. One key challenge Charles Tyrwhitt faced was an enormous variety of different products, with only 8% receiving the marketing investment needed to drive sales. Upp’s operating system rapidly increased this figure to 89%, leading to £1.5 million in additional revenue and a 14x increase in ROI. Over time Charles Tyrwhitt has enjoyed a 10 x increase in revenue from its Google Shopping channel.

“With so many product lines, it was impossible for us to manage and at the same time get the valuable insights we need to unlock potential and find hidden opportunities to improve. Upp changed all that and now we can spend more time using the insights to influence and support business decisions and activities.”

Joe Bloomfield, Head of Digital at Charles Tyrwhitt

It was a similar story with home and lifestyle business Nkuku, which started out as a wholesaler dealing with independent stores across the UK, before growing into a major presence online, selling directly to its customers. For years, Nkuku engaged an external agency to manage its digital advertising. But with an inventory of over 1,600 unique SKUs, there was a huge discrepancy between the products generating the most income and the products being advertised. Products generating 15% of Nkuku’s total revenue were only getting a 1.7% allocation of advertising spend, while products generating 0.3% of total revenue were getting 9%. Within three months, Upp had turned things around, leading to a 37% increase in sales volume, and £230,000 more in monthly incremental revenue. 

“The Upp. platform automatically makes improvements to our campaigns meaning changes are implemented quickly to achieve and maintain our targets.”

Adrian Flowers, eCommerce Director at Nkuku

These results illustrate the impact that Upp. has for retailers across the board. Using decision intelligence to see where things are going wrong, and automating what’s needed to get them right on Google Shopping. 

Stop guessing and start using your data

At its core, Upp. gives retailers the peace of mind that their Google Shopping channel works for them – not against them. Retailers have much of the data they need to improve their marketing channels and Upp. decision intelligence makes this happen. By combining retailer data with Upp. retailers become certain that each Google Shopping advertising optimization is contributing to the right business objectives. And through Upp’s unique retail decision intelligence, you can reduce the total cost of operations, whilst reliably scaling Google Shopping. You have the data that you need to justify decision-making and align financial and marketing goals.

Since its launch in 2019, Upp. has grown to handle more than 102 million retail products and generate over £625 million in revenue for retailers globally. But we’re just getting started. To find out more about how Upp. will help your business become more efficient, more effective and more profitable, get in touch .