Algorithmic trading vital to optimizing sales on Amazon

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Amazon bested even its own records on Prime Day this year, as sales hit $10.4 billion, a 45% increase over 2019 and nearly three times the sales of the year previous.

Paul Palmieri

While there were many wins from brands both big and small, the statistic that you won’t read about in any press release is the amount of money spent on advertising those products. To stand out, brands needed to boost their budgets for sponsored ads by as much as 200%. But that money didn’t go as far; the average CPC for sponsored brand ads was up 23% on Prime Day year over year.

If you’re a brand trying to leverage Amazon to sell your products, you can’t just rely on high-volume sales events and increased ad budgets. And you can’t be making your decisions (e.g., pricing, inventory, ad spend) based on one-off, time-lapsed or siloed data.

First, you’ll break your brain trying to crunch all of those numbers — and leave your teams exhausted, unable to focus on what they do best. Second, even if you had your entire team working on these problems, it still wouldn’t be enough. At the level of data and speed that success in today’s e-commerce environment requires, the human brain just can’t keep up, let alone get ahead.

You need to start making technology work for you, and a real-time operating system can help you pull levers to optimize for KPIs (like net margin) that drive real business outcomes. Here’s why this will be critical for your success:

Unlock your data, which is now trapped in black boxes

The problem we have today is that most brands, whether they be DTC challenger brands or iconic CPGs selling omnichannel, have more data than they know what to do with. But they are lacking intelligent data warehousing, and, more importantly, they are lacking a platform that can tie all of the data together.

It’s not just about data, though. Brands today do not have full transparency or visibility into their entire e-commerce value chain. Most are juggling multiple technology platforms, with areas like sales/retail, marketing, finance and operations all running in disparate silos.

So when you go to make decisions about how much to spend or distribute on Amazon, you don’t have the data you need (e.g., demand forecasts, quantitative shopper insights) to make those decisions.

Algorithmic trading allows you to optimize to stronger KPIs

Another reason why most CPG companies today have had their margins squeezed to the bare minimum is because they haven’t been optimizing for net margin. Instead, they’ve been pulled in different directions, with one machine telling them to increase or decrease their ad spend here, another telling them to beef up the inventory of a certain SKU at a certain time.

While the individual technologies are great to manage each of the departments, unless they are integrated together, they won’t move the business forward, with a complete and total focus on profitability. In these times, it’s not enough to just grow your top line — you must grow your bottom line, too.

Here’s an example: A pet care brand selling online was spending a significant amount of money on PPC on nonbranded category search. They could have just kept spending each month, looked at the reports that showed they were getting a return on ad spend (ROAS), and called it a day.

But ROAS is no longer a viable metric for success. Instead, this company executed the campaign with real-time optimization leveraging a platform that broke open all the “black boxes” of data and integrated performance metrics, so they could know for sure that their ad dollars were going further. They saw CPC efficiencies created, and higher organic search ranking due to newly created demand.

More importantly, while their ROAS was measured at 42%, they saw a 372% top-line revenue growth — and a 2% net margin growth. While 2% might seem small, it’s higher than zero, or even negative growth — both of which are more common in the e-commerce space.

Real-time decision making and accurate forecasting

When you have digital shelf technology that keeps a pulse on larger market trends, you can actively monitor market fluctuations, and therefore be more nimble and accurate in your responses.

And, rather than just keeping up and being reactive to the marketplace (like a day trader), algorithmic trading will help you plan, using mathematical models to predict future supply and demand, and to guide your e-commerce decisions so you never sell blind again.

Wall Street traders use the Bloomberg terminal to access real-time financial market data. You’re a trader, too — buying and selling on the open retail marketplace — and it’s time to build your command center and leverage the benefits of a quantitative trading platform.

In the next few years, we’re going to see a massive amount of change in the e-commerce marketplace, no doubt driven by the acceleration of technology. The feats of engineering we are seeing today are impressive. The question now is, who will drive those machines? I believe we will see e-commerce teams evolve and talent emerge that will be devoted to a “day trading” approach, which will save countless man hours from what is now a flawed and manual process.

And we will see brands empowered by this. I’m looking forward to the economic power they will achieve due to access to real-time actionable insights to inventory, promotion and distribution — and the ability to optimize both top and bottom line.

Paul Palmieri is cofounder and chief executive officer of Tradeswell.  He can be reached at (paul@tradeswell.com).


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