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Personalized Recommendation: Modern Conversion Strategy For Shopify Stores in 2022

Striving to be a successful Shopify store with increased conversions? Here's why Personalized Recommendations is the strategy you need to offer your customers with a curated experience that keeps them coming back for more.

April 6, 2022
mins read
Personalized Recommendation: Modern Conversion Strategy For Shopify Stores in 2022

Personalized Recommendation: Modern Conversion Strategy For The Modern World

According to McKinsey’s recent survey, in light of the events of COVID-19, it is observed that this global pandemic has accelerated the digitization of the market by several years, and has totally transformed the way people do business for good. More and more people are now shifting their shops online, and as a business owner, there is no going back. If you haven’t adopted these new ways of operating online, then your shop is likely to be extinct soon.

And no, this is NOT an exaggeration.

People are now three times more likely to make a purchase online than they had before the crisis, and now more than 80% of customer interactions are happening online.

Average share of customer interactions that are digital

We know, it’s frightening to an average business owner, who does things offline and follows the traditional market strategies. But the facts and numbers are clear, and we cannot ignore them.

The cat is out of the bag now, and the smart question that you must ask is, “How do I build my business online?”.

For most product-based businesses, where people deal with tangible objects, Shopify is currently THE best option in the market. It has been in this field for years, with an established reputation and a lot of successful clients and satisfied customers under its belt. For those who are unaware of this giant, Shopify is an e-commerce platform where people like you and me can set up an online store, to sell our products through dropshipping or directly.

As of 2020, over 800,000+ businesses use Shopify, capturing around 20 percent of the market share. You will find dozens of success stories depicting huge sums of revenue and cash flow generated per month from this platform if you’ll search about it. But in reality, the chances of success on this platform are too low, if one is not serious about it.

In fact, 19 out of 20 stores fail on Shopify, which is, over 95%.

So now, the question is …

How Can You Be Successful At Shopify?

You may have a great product, excellent service, and an incredible team besides you, but none of it matters in this vast landscape until people discover you. Branding and Marketing are the 2 pillars, upon which the foundation of a successful store is built. Branding makes your products memorable and tells your customers what to expect, whereas Marketing builds never-ending lifelong relationships. And the effectiveness of both reflects in the numbers.

When you talk about your product on social media or run a targeted ad campaign, you are basically inviting people to look into your offerings. Say, 100 people saw your post, out of which 20 people landed on your website, and only 1 person actually bought anything from you. What does it say about your sales page and your marketing funnel?

In this scenario, there are two things to notice: First, your marketing campaign was good, it managed to get up to 20% of people to go to your store. Second, your on-page conversion was not-that-good, since only 1 out of 20 people made any purchase. To improve the conversion ratio of the landing page, you can implement the strategy discussed later in this article.

The one thing you need to understand now is: “Everything boils down to the conversion ratio”. It is the most reliable metric that will tell you the truth about the effectiveness of any strategy.

What Can You Do To Increase The Conversion Ratio?

Increasing the landing-page conversion ratio is a tricky game. For its optimization, people deploy several strategies such as analyzing the heatmap of customer’s mouse activity, designing minimalistic layouts, using a contrasting color scheme, etc... But none of them perform as well as “Personalized Recommendations” do.

According to a study by Accenture, 2 out of 5 people leave a retailer’s website because they’re flooded with the number of choices available.

Besides an improved customer experience, research shows personalization has a significant impact in increasing Average Order Value, Conversion rates, customer loyalty and allows for a cross-channel personalization experience.

Today, brands have the power to analyze their customer’s behavior and data, to spontaneously provide them with a curated experience, according to the context. Yet, not all businesses are leveraging the potential of personalization and are missing out on opportunities offered by the market. Personalization is quintessential to help your customers overcome that unseen barrier, that prevents them from taking any action.

Research says, 91% of consumers are likely to shop with brands who recognize and remember who they are and also provide them with relevant offers and recommendations. To get this accomplished, 89% of businesses are starting to invest in personalization based on indivisualization over segmentation. The results are apparent, as confimed by 75% of marketers. Adding personalized elements has helped increase engagement and return on investments.

Customer state distribution based on study by Accenture

How Personalized Recommendations Work?

80% of consumers are more likely to buy from a business that offers them personalized services, however, 63% of digital marketing leaders lack the correct technology and tools to personalize services. Personalized recommendation engines can be build using several techniques and algorithms, but not all algorithms are created equally. Elementary level recommendation systems, which suggest “similar products”, are usually not as effective as sophisticated machine-learning-based recommendations, that utilize hundreds of data points to predict exactly what you want. Today, most recommendation systems are using cutting-edge deep learning models to pinpoint the interests of their customers, on an individual level.

Such algorithms are taking account of the factors like customer’s search query, demographics, shopping history, items viewed, and so on. These factors then serve as the crucial data points (inputs), which are fed to the deep learning model. The model is then trained on this data until it can reliably predict the customer’s preferences (output) as closely as possible.

Broadly speaking, there are 3 types of filtering in product recommendations:

  • Content-based filtering: Here, the model makes a user-specific recommendation based on the personal data collected such as age, geographic location, browsing history, etc... This filtering adds a thick layer of personalization in the user experience.
  • Collaborative filtering: There are two types of customers you’ll be having on your website - First-time visitors and returning customers. For the first type, you cannot add personalization simply because you don’t have any data. So here, the model uses data collected from other users, who have made a similar purchase as yours, to make recommendations.
  • Hybrid Model: It is a mix of both, content-based and collaborative filtering, where the model uses data collected from other users, who have a similar profile as yours, to make recommendations. This model provides the highest accuracy and conversion boost.

Benefits of Personalized Recommendations

After hearing about all the technicalities, you must be wondering, Is it really worth it? And the short answer is YES.

According to Barilliance research, “Product recommendations account for up to 31% of e-commerce revenues. On average, 12% of customer’s sales is attributed to recommended products”

In the same research, they also found that customers are 4.5 times more likely to add recommended products to their cart and 4.5 times more likely to make the purchase.

Increase in AOV with Recommendations

As you may have guessed by now, personalized recommendations, such as “Frequently brought together”, not only increase the likelihood of a successful transaction but also, increases the Average Order Value (AOV) per customer. That means customers end up buying more (recommended) products from you than they had originally intended to purchase.

There are several other benefits of implementing personalized product recommendation too, such as:

  • “Recently viewed” suggestions and  tell customers to look for the items they hadn’t thought of in the first place.
  • “Featured recommendations”,
  • “Recommended for you” suggestions establishes a deeper connection with the customer, when you use their name directly.
  • Personalized product recommendations reduce cart abandonments by 4.35%.
  • It increases the chances of returning customers, increasing loyalty.
  • Recommendations such as, “Customers who bought  also bought ” present the social proof for other relevant products that a customer might purchase.
  • Suggestions based on previous purchases () increases the opportunity for up-selling and cross-selling.
  • “Since you already own this, you may also want this”

All in all, personalized recommendations lead to lesser cart abandonment, better user engagement, and keep visitors coming back again and again.

So how do you implement personalized recommendation engines, you asked?

Adding Personalized Recommendations to your Shopify Store

One of the major problem that every shopify owner faces, because of the extremely competitive nature of the platform, is his/her customers leaving the store website without making any purchase. Either they’re not finding the right product instantly or they’re having a decision paralysis due to the overwhelming number of choices. Regardless of what it is, it is your job to remove that barrier and help your customers navigate fluidly. And personalized product recommendations is the key for doing so.

According to the official Shopify website, to add product recommendations, you need to add a new section on the product pages which will show you the auto-generated product recommendations. There are many personalized recommendation engines out there and, we’re proud to say, ours is one of the best. We use latest AI/ML technologies to provide customers the best possible recommendation to boost conversions and increase AOV.

Some of our offerings include:

  • Advanced Analytics
  • Smart “Related Product” recommendations
  • “Frequently bought together”
  • “Customers also bought” suggestions
  • Best 24x7 Customer Service Support and so on

Set up best personalized recommendations with us. Get started with a few clicks. Sign up today!

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