Data-Driven Marketing for E-commerce

By Asiya Nayeem / May 31, 2021

5 min read

How effective is your marketing strategy? Sure, you may be able to tell us how large your Instagram following is or the click-through rate for your newsletters. For many brands, marketing is a whole lot of guesswork and some surface-level analytics. But that doesn’t need to be the case. We’ve got the secret sauce to make your marketing drive more conversions faster— marketing powered by data science.

All marketers know that tapping into your data and using your data to improve your marketing is key to improving, optimizing, and driving more customers to your business for immense growth.

Today, we’re making the case for marketing that is powered by data science, and through this article, we hope to give you some key ideas to help you implement a data-driven approach to marketing, without having to hire a single data scientist. (Yes, it’s possible!)

What is Marketing Powered by Data Science?

Data science marketing is when a marketer applies data science modeling to better understand customer interactions, behavior, product, and overall store performance to optimize marketing campaigns. By powering your marketing efforts with data science, you are constantly running your conversion through models that allow you to monitor the performance of your activities, run tests to maximize your performance, and tweak your marketing strategy at a pace that is far quicker than the average marketer. With this strategy, data is at the center of your growth, rather than just a second thought.

Let’s take an example of how data science can take marketing to the next level. A sneaker brand is running an ad about their latest product launch. If they run the ad to be shown to all shoppers who showed an interest in sneakers, they would be generalizing their ad to an audience that is interested in their product category but not necessarily interested in buying that specific product from their brand. This kind of marketing results in high ad spends and low returns on investment.

But, if this sneaker brand adds data science to its marketing, that brand would be able to very quickly identify which audiences are interested in buying sneakers from them. They would be able to very quickly identify audiences with a high probability of converting and audiences with a higher probability of spending more on their products. By targeting these kinds of high-intent audiences, the sneaker brand would be able to grow and scale online profitably, without compromising its ROI.

How Marketing Powered by Data Science Helps E-commerce Brands

Let’s take a look at the different ways your marketing approach can improve with data science and ultimately help you grow and scale online profitably.

1. Use conversion data and website behavioral data to find new audiences with high intent

When a web visitor lands on your site, that visitor brings in hundreds of variables through their digital footprint. Such data is stored in applications like Google Analytics. It is humanly impossible to manually analyze and model every variable of every web visitor to find your most profitable direct and indirect audiences for marketing campaigns.

However, using data science models powered by artificial intelligence, you can very quickly analyze all the variables of your web visitors and learn a lot about your potential customers and their affinities or interests. This kind of analytics allows you to easily understand which new audiences have the highest probability of converting, why customers interact with your store, what causes them to engage with your brand more, and what makes them drop off.

This kind of information is powerful. You can improve your on-site experience, craft messaging that appeals to them better, and set up marketing campaigns that do not include general rules, guesswork and/or biases. By understanding your customers, you’ll be able to sell your products better and improve your returns at every stage of the funnel by always marketing to audiences with the highest probability of converting or spending big on your site.

Check out this example of how a brand found new audiences by incorporating data science in their marketing.

2. Understand your remarketing audiences

All your website visitors are at different stages of the buying journey and have different needs at each stage. So, a marketing message that makes one customer click could make another one click away from your brand.

Therefore, understanding which remarketing audiences have a higher probability of converting is important to ensuring that you aren’t spraying your marketing spends but targeting the right audiences based on their intent to buy, needs, preferences, and behavior. By applying data science to your remarketing, you’ll be able to drive higher conversions faster without changing your ad spend.

With data science powered marketing, you aren’t throwing strategies at the wall, hoping they would stick. You are instead using proven insights to set up ad campaigns that are sure to work and help you win customers through remarketing.

3. Track high influence products

If you have a large catalog, chances are that you might miss products that are have high influence with little or no paid marketing. Using data science, brands can very easily identify which products have high organic influence and track the potential conversion rate of those products could have compared to the average conversion rate of other products that are being marketed. Marketing teams can then use products with high organic influence in very creative and strategic ways to attract new audiences or convert website visitors/cart dropouts.

4. Know which existing customers to target at any given time

Every brand knows their loyal customers. Every brand knows their big spenders. However, with data science, marketing teams can very quickly and easily identify who from their Loyal Customers and Big Spenders is most likely to buy something from the brand in the next few days/weeks/month. Moreover, using data science, marketers can identify which of their customers are most likely to become loyal customers in the next few weeks – if they engage with them correctly.

Here are a few scenarios that explain how these insights can be useful to marketing teams. For example, if an online fashion brand releases a new fashion line and they want to launch a marketing campaign to existing customers who are most likely to be early adopters. Using data science, that marketing team can figure out which of their loyal customers are most likely to buy something from them in the next 30 days, and they can launch a marketing campaign showcasing their new line to this specific group of loyal customers, they have a higher probability of converting than the others.

By using data science in this manner, marketing teams can improve their bottom funnel marketing return and improve the conversion rates and average order values of strategic marketing campaigns.

5. Optimize existing ad campaigns

One of the biggest pain points for a marketer is low click-through-rates (CTRs). But, without any insight into what isn’t working within their marketing campaigns, many marketers tend to just scrap the entire campaign and structure a campaign from scratch.

But you don’t need to! Using data science, you can understand problem areas within your existing campaigns and easily make changes.

Using customer lifetime value and attribution models, data science can easily help digital marketers optimize their campaign by modeling their campaign data. Data science marketing applications like Alavi.ai tell digital marketers where to increase bids, where to reduce bids and which ad groups to pause based on Life Time Value and attribution to help brands achieve their marketing goals.

How Do Brands Start Applying Data Science to Their Marketing?

There are several ways through which brands can start incorporating data science in their marketing to grow and scale online without fear.

In large companies, one of the most common methods of incorporating data science in marketing is to develop in-house technology with data science models that can analyse customer and web visitor variables captured and stored in applications like Google Analytics. But not every brand can afford to build in-house data science models for better marketing, and some brands may not even want to make such an investment even if they have the funding. And that is perfectly alright because of SaaS applications and technology like Alavi.ai.


To start using data science in marketing, many digital marketers use technology like Alavi.ai. Alavi focuses on enabling digital marketers to find new audiences and optimize ad campaigns using data models.

To learn more, request your free Alavi demo and trial!