Online advertising isn’t the only way you can increase your revenues via digital marketing. In fact, it may be one of the most inefficient ways to do so, depending on the campaign. More than half of a business’s digital marketing comes from their website. This is how you attract, engage, and maintain your customers. Creating a positive online experience can even contribute to higher revenues when implemented effectively. One of the most effective ways to accomplish this is through a personalized recommendation engine that upsells customers and increases average order value (AOV).
The Importance of Customer Experience
Nothing is more important for a growing business than providing consistently positive experiences. If a customer has a negative interaction, it may significantly threaten their customer lifetime value (CLV) i.e., the duration, frequency, and value of purchases over their lifespan. This is why experiential investments are so valuable and why they have taken the forefront for many enterprises.
Customer experiences have transitioned from pleasant add-ons to competitive advantages to fully-actualized products. Now more than ever, companies are trying to leverage positive user experiences to improve the scope and reliability of their revenues. As of 2018, more than 89% of companies were competing on customer experience alone. That statistic is more than 50 percentage points higher than it was back in 2010. This recent transition to experience-driven services is largely due to the rise of digital marketing.
Every visit to your website is an experience that affects your company’s relationship with that visitor. Post-COVID, the value users assign to their site experience has only increased. According to a recent report, 59% of consumers care more about customer experience when it comes to purchasing than they did prior to the pandemic. Considering the impact each click has on a corporation’s bottom line, it follows that the marketing team should afford the same attention to optimizing that experience. Recommendation engines are a cost-effective way to accomplish that as well as increase online revenues through improved AOV.
How Recommendation Engines Improve AOV
A 2019 study published through the Journal of Retailing and Consumer Services explored the utility of recommendation engines (RE) in increasing the likelihood of visitor purchases. Some of the metrics used to measure the success of RE in this pursuit were average monthly revenue, AOV, and items per order (IPO). The model created by the researchers combined a blend of selling strategies to deliver “personalized marketing information concerning the recommended items for online and offline customers, using a blend of strategies.” All of these aim to increase e-commerce revenues.
This experimental study used quantitative research methodology to evaluate the tangible impact of RE on a mid-sized healthcare retailer based out of India. Null-hypothesis testing was used to determine the quantity of influence RE had on revenue and AOV.
The study’s results presented strong evidence to support one of its initial hypotheses that “the more the business performs personalized digital marketing, the higher the rate of AOV.” The introduction of an effective recommendation engine resulted in a 32.79% increase in AOV over the three-month testing period. That means – on average – every order will be increased in value by 32%. If you’re focused on longer customer tenure with higher shopping frequency as part of your CLV efforts that give you a multiplier effect. Instead of just one order being worth 132% more, multiple orders per customer are increased by that amount!
How to Effectively Integrate a Recommendation Engine
The efficacy of a recommendation engine is determined by the sophistication of its algorithms. If you have a simple recommendation engine, it may not maximize your CRO to the same degree. This is because the quality of recommendations is less accurate and, therefore, less conducive to higher conversion rates. Unfortunately, a powerful recommendation algorithm can be worth millions of dollars and is what companies like Amazon and Netflix have invested a significant amount of time in perfecting.
But there are still options.
For online retailers, there are various third-party developers who license their recommendation engines out to their clients. Organizations like Stradigi AI use machine learning to elevate the sophistication of their recommendation engines. This is a great solution for creating suggestions for cold start customers. Moreover, companies like Shopify offer recommendation engines that are easily integrated into your existing web platform. Though, this alternative is not individualized to your audience or industry.
Accounting For Cold-Start Customers
But what about cold-start customers? A huge part of digital marketing is search engine optimization (SEO). The goal of SEO is to maximize the amount of consumer traffic a site receives from various search engines or platforms. If your business’s SEO is strong, then your site will receive a substantial amount of cold-start customers. These are users, as mentioned above, who do not use an account to make purchases. This makes developing an effective RE that much more difficult.
The only way to overcome the challenge of cold-start and window-shopping customer segments is by collecting as much customer data as possible. This can be one of the driving reasons why small businesses are less likely to introduce such an effective marketing tool. Costs and resources can be hard to collect and utilize if you don’t possess the necessary experience. For instance, Yuspify notes that even the first 2 to 3 clicks of a user’s visit can provide valuable information for overcoming the cold-start dilemma. Fortunately, enterprises can leverage the existing data systems established by different data firms to fully optimize their website and customer experiences. In doing so, companies can introduce automated recommendations at different shopping points to entice every customer segment.
While there are many digital marketing strategies, none provide as effective and permanent a solution as recommendation engines. If you want to increase revenue and CLV by improving AOV, adopt a recommender system for your website. Follow Techdee on social media!
Ron Bisaccia is Managing Director at Enabled Concept. They leverage a world-class data science team, cutting edge tools and techniques to generate measurable value for your business. They have a track record of proven results with Fortune 500 clients and we’re committed to producing the same results for you.
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