Recommended actions are derived from prescriptive analytics, a type of analytics that doesn’t just tell you what’s going to happen but also what you should do to maximize the outcome you want. I mean, imagine being able to reduce errors and mistakes with the help of AI-driven analytics. That’s what recommended actions are all about. And in this blog, I’m going to be showing you 5 ways you can apply recommended actions to your ecommerce marketing strategy to increase your KPIs.

  1. Profitable new user acquisition

Finding traffic to your store isn’t so tough, but finding quality traffic that is more likely to convert certainly is. You have to know who to target with which type of content across what device at what time and what are they bringing for Thanksgiving dinner? You get the point. But with analytics, you have the upper hand. Machine learning enables ecommerce marketers to identify patterns and trends amongst a huge amount of customer data. And because of this, marketers can now predict the purchasing behavior of potential buyers and store visitors. But what I just told you is actually just a prediction. With recommended actions you can take it a step further and know how to engage with each customer, which offer, channel, device, and content offering you should be delivering. 

As a result of applying these recommended actions, you will be able to:

  • Allocate your budget to channels that convert customers better than others
  • Reduce costs by targeting customers most likely to convert and not wasting marketing spend on those who aren’t
  • Lower the CAC
  • Increase revenue and profits
  • Increase conversion rate
  • Expand your reach to new target audiences and potential customers
  1. Increasing LTV

Ah yes, one of the most verbally overused and underrated metrics in all of marketing. LTV. This metric is key in distinguishing the financial value of each customer. Identify those who are more valuable and use analytics to find insights on which segments or customers you need to spend more time and resources on. And if you’re able to predict which customers are going to make a purchase and how much, you can always apply some upselling and cross selling techniques to get them to purchase more, now that you know they’ll be converting anyways. Recommended actions will take you one step further and guide you on things like what channel do you approach each customer to maximize sales? What type of promotion and when? Which customers should you target and how (one customer at a time)?

When you leverage your recommended actions you can:

  • Figure out which types of customers are more valuable to acquire
  • Decide which current customers to focus more attention on
  • Estimate the total value of the customer base (one user at a time)
  • Identify first-time buyers who are likely to convert and encourage the second purchase with an offer
  1. Managing loyalty

As marketers we all know that it is so much more expensive to acquire a new customer than retain an existing one. It’s also pretty hard to get your customer to come back again and again, right? Maintaining loyalty, increasing retention, reducing churn- whatever you want to call it, this is key in the success of an ecommerce business. These types of companies are highly dependent on loyalty. And if you can’t identify who is at risk v who isn’t, it could be super detrimental to your business and cash flow. For example, if you incorrectly assume that a lot of happy customers are going to leave, you’re going to end up wasting a lot of money offering discounts to customers who were never at risk and didn’t need this special incentive. 

With machine learning, you can know which customers will soon cancel their memberships or subscriptions, not return to make another purchase, or if they’re planning to leave. With recommended actions, you can filter users from most to least likely to churn, and focus on those who need the most attention. Discover who you should reach out to, how you should engage with them, and what content you should promote to keep them loyal.

Benefits from these types of recommended actions include:

  • Save costs by giving discounts to the right users (those on the brink of churning) and don’t waste revenue on those who aren’t planning on churning
  • Increase retention & loyalty
  • Increase LTV
  • Increase revenues
  • Increase sales
  • Highlight those who are most likely to churn and take care of their needs early.
  • Identify first-time buyers who are likely to convert and encourage the second purchase with an offer
  1. Campaign optimization

Campaign optimization is probably one of the most dynamic aspects in marketing, in my opinion. Since its introduction back in the early 1900’s, the way we have managed to move from mass marketing to such hyper personalization is still crazy to me. And it gets even more precise and more targeted all the time! Well, a lot of that is due to programmatic technologies but a lot of those technologies are founded on machine learning. You see, with machine learning you can predict whether or not a certain offer will be accepted by a (potential) customer. It knows, for example, if the customer is excited, exactly what type of content to show and at what time to get them to click or convert somehow. That’s a lot of what recommended actions do for campaign optimization. They help ecommerce businesses understand which customers to target with which campaigns across what channels at what times to be most effective (one customer at a time).

Once again, recommended actions prove to be hugely beneficial for ecommerce businesses as they let them: 

  • Remove redundant communication to save time and money by targeting fewer customers while achieving similar profits
  • Allocate resources more efficiently and effectively
  • Identify those that are ready and help them finish their session with a purchase
  • Reach out to previous customers who have bought, abandoned a cart, or just browsed your website with campaigns that will convert
  • Increase conversion rate
  • Lower CAC
  • Lower costs and increase revenues
  1. Maximize AOV

The more our customers spend, the better off we are, no? With machine learning, you can predict which products are going to be purchased the most, which combinations of products will be most popular and what the average order value will be. Recommended actions you will know which products to promote and to who in order to increase chance of sale and AOV, discover which user segments you should target with personalized offers so they make their first purchase and how to show your products based on browsing behavior to make the shopping experience relevant on the first visit.

Recommended actions let you:

  • Identify active buyers who are likely to convert, then provide an offer most likely to secure the purchase and increase the cart value.
  • Remarket with dynamic upsells and cross sells
  • Increase AOV and sales
  • Increase conversion rate

Recommended actions are the key to future success. They help ecommerce marketers with profitable new user acquisition, increasing the LTV, maintaining loyalty, optimizing their campaigns, and increasing the AOV. Let’s face it, business decisions driven by AI are much more likely to succeed than decisions based off of assumptions or gut instinct. To learn more about what recommended actions can do for your business, reach out to us today!