4 Ways to make the most out of Algorithmic eCommerce
A millennial consumer scrolls through her Instagram account and an ad about chic jewelry catches her eye - she gets excited as it matches her tastes, she opens the brand or marketplace website, and browses through the offers and collections, adding items she likes to the cart, some of which are through recommendations provided by the website or marketplace she is on.
Before ordering, she uses the chatbot to get some information and gets a personalized discount coupon based on her cart value. Subsequently, she places an order and gets her order within the assured delivery time, and becomes a regular customer.
The above scenario may seem like an everyday customer interaction with eCommerce brands but underneath it is the magic of Algorithmic eCommerce that taps into the power of algorithms, data, and dynamic learning. Digitalization and automation have made it possible to use data in real-time, and come up with accurate predictions about what products customers prefer and the best way to reach the customers.
Algorithmic eCommerce is a sure-shot way of scaling your eCommerce brand to the next level while maintaining a one-to-one customer connection. Here are four of the best ways to get the most returns on implementing Algorithmic eCommerce:
1. Target The Right Customers
It’s become important now more than ever to be nuanced about the target audience, take into account their behavior and interests, and craft marketing campaigns that resonate with them. Algorithmic eCommerce enables brands to process vast amounts of data collected through different channels - be it social media channels, the brand website, email campaigns, past online purchase behavior, or any other online source. With this data AI tools can predict precisely how customers will respond to specific ads.
User segmentation based on AI-driven data analysis enables marketing teams to create strategic campaigns. For example, specific keywords that evoke interest or capture attention for a particular user segment can be inserted into ads. SEO can be tailored to a specific customer base while taking into account current trends in the market. Channels with greater engagement can be narrowed down and focus can be redirected towards them for maximum impact.
Since customers go through various touch points such as ads on social media channels, eCommerce or marketplace landing pages, and blog posts before actually making a purchase, this non-linear behavior can be accurately tracked by Algorithmic eCommerce and retargeting ads can be placed at appropriate points to encourage conversions.
AI tools can also be used to monitor the performance of marketing campaigns, they can predict the success of the campaigns and even possible issues with existing campaigns. For example, these tools can highlight when to cut losses in campaigns and reorient marketing strategy to maximize ROAS and reduce CAC.
2. Enhance The Purchase Experience
Excellent customer experience is the core of an eCommerce brand’s success. In particular, how customers interact with the brand website or the marketplace listing directly impacts conversions and order cart values. Additions such as chatbots and digital assistants offer great support to customers. They are available all the time, ensure consistent responses, and can resolve low to mid-level issues automatically.
More importantly, they can provide proactive customer service such as reaching out to customers and creating positive experiences. For example, a potential customer might be browsing through product pages but not adding items to cart, digital assistants can help the customer in finding what they are specifically looking for.
Other features such as Customer-centric search in the form of image search and keyword-based search make it easy for customers to find the items they are looking for. AI copywriting is becoming popular for mundane tasks such as product descriptions. This is particularly useful if your eCommerce brand has hundreds of products and manually updating them would be an onerous and difficult task.
Prices can be optimized dynamically based on supply and demand variabilities. This enables discounts to be passed down to customers where possible. Empowering the customers thus with the right information and timely interactions builds trust and helps retain customers and drive customer loyalty.
3. Up The Ante On Personalization
The way to a customer’s heart is through personalization and then some more personalization. Personalization involves curating and creating experiences that are shaped by the preferences of customers. The wealth of customer data available to eCommerce brands enables Al-driven tools to create hyper-personalized features on the website.
For example, product recommendations based on purchase history, search history, and similar purchase orders by other customers can bring relevant products to customers’ attention quickly. This is highly useful to combat issues such as decision fatigue where a customer spends time on the website but does not end up buying anything due to the number of available items. Moreover, relevant product recommendations also increase AOV.
However, that’s just the beginning.
Dynamic pricing is an excellent way to engage a customer. By pricing a product based on past purchase data and the likelihood of an individual paying for it, you can ensure better conversions and fewer carts abandoned. This makes sure you can remain competitive and profitable.
Returns can be minimized by suggesting the right product to the customer upfront such as recommended size in case of clothing based on previous orders. This not only ensures better customer satisfaction but also reduces the hassle of dealing with returns and managing inventory losses for the eCommerce brand.
AI is also helpful in the retention of customers as personalized newsletters with offers on items specifically pertinent to a customer can be created, relatively easily and at scale. This is just the tip of the iceberg, as more and more data is captured from various sources and analyzed, greater insights into how personalization can help reach customers better will materialize.
4. Increase Operational Efficiencies
Algorithmic eCommerce helps to automate, manage and optimize the business operations and processes of eCommerce brands. These could be routine and repetitive tasks or even the most complex decision-making processes that usually need manual intervention. It could be automated order tracking and providing regular updates to customers. It could be automating inventory sync whenever items are in low stock or out of stock.
The entire supply chain can also be digitized whereby logistics can be managed in real-time through data from devices such as RFID tags and sensors. This increases operational efficiencies of the eCommerce brand by reducing processing times and reducing costs. Unexpected issues such as delays in shipping can be communicated to customers at the earliest. This onus to proactively keep the customer up-to-date greatly improves customer experience and increases brand reliability.
AI tools also have multiple spillover effects such as increased productivity, and insights derived from them aid in informed decision-making such as when to launch new products. Recommendations delivered by an algorithmic eCommerce platform can
greatly improve the outcomes of marketing campaigns and ad busgets,
help brands optimize content for better performance, and
help take decisions on product and inventory.
As technology keeps evolving, eCommerce businesses have to keep themselves updated on the digital front. Setting up an eCommerce business has become easier than ever, how each eCommerce brand differentiates itself from the crowd and delivers for the customers makes all the difference.
Algorithmic eCommerce puts available digital resources to smart use. This can lead to transformational effects for the eCommerce brand, helping it thrive in both good times and times of uncertainty and creating a happy, loyal, ever-growing customer base.