Starting an e-commerce brand has never been easier; anyone with a product to sell can have a Shopify or Woocommerce shop running within a few hours. Yet, it’s never been harder to actually grow and scale. You must find your customers on multiple channels and take orders from them on multiple platforms.

As an e-commerce owner, it’s no longer enough just to have your own website. On average, one brand needs 10-12 tools to run its business with thousands of data points to parse through. Add the backdrop of rising interest rates, inflation, and customer sophistication, which have increased customer acquisition costs (CAC); it becomes a vicious cycle where the odds may feel against you as an e-commerce owner. 

Enter AI. 

AI is an enabler that can help solve a number of pain points and help reduce resource and time constraints for young D2C brands. Here are a few successful use cases for implementing AI for your e-commerce brand. 

Using AI to parse and provide actionable insights

New e-commerce brands today are overloaded with data. It is a whole lot of noise. With CAC as high as in the US$100s per customer and customers spending less but expecting more, leveraging data to find the right customers and deliver targeted and effective marketing campaigns is even more important today.

You can connect your most-used data sources such as Shopify, WooCommerce, Meta Ads, Google Ads, Klaviyo, and Google Analytics so the AI can run different growth scenarios and analyses within seconds using your data but also comparing it against reasonable benchmarks for brands like yours.

This allows the AI to predict areas of focus where you are likelier to grow and succeed and customers better suited for you. It can then provide actionable insights in those areas, utilising a database of tactics prioritised on factors such as estimated uplift, effort required, and other factors based on your brand and industry. 

Also Read: Why fintech companies should learn about customer retention from e-commerce companies

The other thing to note is that customer personas are no longer about demographics; for example, creating campaigns based on age and socio-demographics. We are now shifting to indexing more on the use case, e.g., what am I buying this product for? That can span different types of people or personas.

For example, one of the brands we work with is a skincare anti-ageing brand. This product may seem geared toward a slightly older demographic on paper. It would be very easy to come up with a traditional marketing segmentation (e.g., female, ages 35 to 54 years old, etc.) and launch an ad campaign based on that segmentation. 

With the predictive capabilities of AI, we found that younger age groups  (e.g., 25-30-year-olds) would likely be keen to use the skincare brand for preventative care, and the same group was also interested in pop culture and celebrities. The AI can then prescribe to target 25-30-year-olds and develop an ad campaign and creatives that touch on today’s pop culture trends. 

Using AI to find the right customers: Your ‘better’ customer

A common question brand owners ask is, “Where can I find more of my better customers or the right customers?” AI can help you build a profile of your ‘better’ customers, i.e., customers who will buy, stick around, and ultimately, be profitable.

AI can produce such a  customer profile. AI can tell you what they look like, what they are likelier to purchase now and in the future, and where they could potentially come from.  It can actively trawl and look at available channels to access customers, social media sites, affiliate marketing players, and other marketplaces. The result is that it will tell you that “your ‘better’ customer looks like this type of person, and you can find them in these places.”  

For example, for one of our organic food brand customers, the Needle AI figured out similar interests that the ‘better’ customers of this brand might favour, such as holistic health and home gardening. The AI recommended a prospecting campaign using interest targeting on Google Ad platforms, and they saw a return on ad spend of 8x instead of their usual 2x. 

Using AI to increase customer stickiness

Retention is a pain point for most brand owners. Assuming you have a good product, theoretically, getting the customer through the door is more expensive, though it should be cheaper the second or third time around, and that’s where your profits come in.

Also Read: How express delivery services can become a key differentiator for e-commerce businesses

But, the challenge lies in getting the better product in front of an existing customer at a better time while wading through all the noise that we’re all typically bombarded with from all angles. 

With the predictive abilities of AI, it can develop a view of what customers are currently primed for another purchase from your brand, what product they are likely to buy next, and what channel is best to reach them with. 

At Needle, one of our brands provides fashion accessories worldwide to women in urban areas. It predicted the likely products existing customers would return and purchase the second time and within how many days of their first purchase. It recommended they set up an automated campaign that sends an email to existing customers after their first purchase of specific products.

The email was among their highest converting ones (converting 70 per cent higher than their average email), generating thousands of dollars of monthly revenue in “set and forget” mode. 

AI can help you do more with less

Velocity matters when scaling a D2C e-commerce brand, and success is about the number of smart bets you can take quickly. As a brand owner, you are in the business of gambling whether you know it or not (note: we do not endorse actual gambling!). Your ultimate success ultimately correlates with how many smart bets you can take as quickly as possible. The AI technology being developed today allows you to take these kinds of bets. 

At the same time, young D2C brands are often resource-constrained — with the founder wearing multiple hats. Using AI, we’ve seen the output in terms of the execution of a team three or four times their size. All this allows you to take a higher volume of smarter bets, giving you a higher chance of success and defying the odds. 

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