We all do better when we know better. But oftentimes it’s harder to know better at critical moments when we have to make instant decisions with not enough information or time. That’s why predictions are good. The help eCommerce marketers gain the future insights they need to make better marketing decisions today.
Predictions are derived from machine learning, an analytical process which leverages historical shopper, pricing, product, and sales data to detect patterns and trends that result in optimal outcomes for your business. With the ability to predict our average order value (AOV) for instance, we are able to plan ahead, be proactive, and allocate resources accordingly in order to maximize our store or website’s revenue. Let me emphasize this again. Predictions are really, really important for us marketers, especially if we want to be readily prepared for the future and have a competitive advantage. Having the ability to predict is the first step to success.
In this article, I will be explaining how predictions can help eCommerce marketers increase and improve their average order value and become phenomenal marketers.
As all marketers know, there are two main ways to increase your AOV:
- Encourage your shoppers to buy more items
- Encourage your shoppers to buy more expensive items
This sounds much easier said than done, I know, but with a little help from predictions, you can encourage your shoppers and website visitors to do both, driving up your AOV. So, how exactly can predictions help raise this valuable metric?
The biggest business goal for retailers is to get as much revenue as possible, and predictive (what will happen) and prescriptive (what you can do to improve it) analytics can help you maximize your store and product pricing while still maintaining high conversion rates and sales. And the reason we need predictive and prescriptive analytics is because there is so much data, variables, and factors that come into play with eCommerce price optimization, it would be absolutely impossible for a human to do on their own! Trust me, our brain doesn’t work this fast.
So how does this impact your overall AOV? Think about it, with predictive and prescriptive analytics you can maximize the price of each product and spend of each shopper while also maintaining high sales. You will be able to sell the same, or more, but with better pricing thus increasing your AOV. Now is that efficient or what?
What does it mean to apply predictions to segmentation? Predictive and prescriptive analytics enable eCommerce marketers to turn mass segmentation into segmentation on a per-shopper level. I’m legit talking about predictions and recommendations for each unique shopper. Additionally, they will tell you which shoppers are most valuable and will most likely react to your marketing campaigns (in addition to informing you which campaigns you should send to which shopper), enabling you to not allocate your budget to those with the highest return and reduce spending on those less likely to buy, but also know who to target and for an increase in sales and conversion rates. And remember the two main ways to increase your AOV? This is all about the first one, increasing sales. Better target your shoppers with accurate segmentation and maximize each interaction. Know what they want to buy from your website before they do 🙂
Just like how predictive segmentation will tell you which shoppers to target, predictions also come in very useful when understanding where to deliver your campaigns and which campaigns, offerings, and messaging will be most effective for upsells and high conversion rates. Once again, these 2 analytics combined are able to provide you with insights on a per-shopperlevel, not mass segmentation level. When you are able to predict which marketing channels will bring in the best results for each shopper and which types of content, products, or messaging to deliver for increase upselling, you are able to not only sell more items, but often encourage the highest spending shoppers to upgrade to a more expensive version of what they are planning to purchase.
When you utilize predictive and prescriptive analytics to increase your AOV, you are creating an AI-driven strategy more effective, efficient, and accurate than any human assumption. There is so much data out there that it’s impossible for us to analyze it ourselves. But with the help of machine learning, we can identify important trends and patterns that benefit our overall AOV. Predicting pricing, segmentation, and marketing campaigns are just a few ways you can leverage predictive and prescriptive analytics for your own eCommerce marketing goals!