Technology is everywhere – it’s the reality of the world that we live in. From self-driving cars to automated bidding software, many decisions are made with the support of a computer-based analysis. The reality of the situation is that despite the advances made over the past couple of decades, we are still not at the point where technology can lead the charge across all decisions. 

Here at Momentum Commerce, we embrace technology as not just a necessary part of our jobs, but as a right hand to help us best serve our customers. We are building a Data Science and Engineering team of the future, supported by some of the best and smartest people we know. We are also dedicated to building a Media Services team that matches up perfectly with the outputs of our DSE team, combining human knowledge from a combined 20+ years in the ecommerce industry with world-class insights from our deep data lake to create the perfect balance.

Automated Bidding is Great – But Not Everything

Changing individual bids across hundreds (or thousands!) of keywords is not the best way to use human brainpower, but we also can’t rely entirely on technology to determine the best bid. While much of the calculations and data analysis is best suited for software, understanding the why behind making a bid change is just as important. Even the smartest bidding platforms have to be informed with the goal of each bid change – are we working towards an efficiency, volume or spend target? Perhaps we are trying to gain market share for a specific keyword? Having the why determined by the human and the how implemented by the machine is the best solution for accurate bid adjustments.

Discovering Competitors

Another example of where machine meets human intuition is through discovering competitors in a marketplace. If you are a brand owner, chances are you have a good idea of who your top competitors are, at least those who sell the same (or similar) products to yours. However, in an online marketplace, those same brands might not be your biggest competition! Data analysis allows us to see the competitors for specific keywords, categories and demographics, expanding the ability to launch successful competitor conquesting campaigns. 

Preparing for Seasonality Swings

What will the impact of a seasonality swing do for your business? In the current retail media landscape, this continues to be unknown. Forecasts to anticipate seasonality swings are built upon multi-year projections to be one step closer in figuring out what will take place but we are still encountering a human error. This is where technology comes in. Using deep data to create historical trend mapping that informs insights allows for us to more accurately anticipate trends in seasonality swings. With the expedited growth of both established and emerging retail media platforms this will be an essential piece of the pie in understanding yearly performance.

Exploring and Mining New Keywords

If we were to leave keyword mining strictly to technology, we would likely add some interesting and not super relevant keywords to our manual campaigns. This could be for a variety of reasons – a misspelling could bring someone to your product despite a search that isn’t relevant to your product, or it could be a term that’s close to your product but not quite your offering. For example, if someone searches for a “twin bedspread” but your product is a full bedspread, you would not want to bid on “twin bedspread” even if that search did result in a sale of your product.

Building Long Term Partnerships

Partnerships are built by a mutual investment in the relationship rooted in trust and genuine goodwill towards one another. Can you replicate these qualities with technology? For Short Term partnerships and interactions, potentially – but not for the Long Term. To move a relationship from Short Term to Long Term you need shared experiences, either positive or negative, where you both agree to continue the partnership after, and technology does not provide those types of experiences. You cannot have a Long Term relationship with one person or force a relationship onto another. 

This is where the nuances of understanding the complexity of the retail media landscape and how to build a partnership rely solely on a best-in-class services team. Their role is to understand their client’s business and how to implement technology within all retail media platforms to lead problem-solving, implementation plans, and most important goal over achievement. Technology cannot replace a warm hello over the phone that is an expert in retail media yet, but it is an intricate part in helping those that do.