Does Personalization Through AI And Machine Learning Help Enhance Market Relevance and Growth?
Jun 09, 2022
10 min read
Table of contents
- How can AI and Machine Learning improve direct-to-consumer marketing strategy?
- Benefits of using the power of AI and Machine Learning in marketing and personalization
- How can ML and A/B testing help you improve direct-to-consumer eCommerce business?
- Examples of Brands using AI and ML to improve their customer service
- Integrate The Mix of AI and ML Into Your Business
In this dynamic D2C eCommerce landscape, the way of shopping is continuously changing. 3 out of 4 customers are likely to shop from a DTC eCommerce brand that provides personalization. Why? Personalization makes customers feel that the brand cares for their special and unique needs and understands what they want to buy. It increases the trust and bond between customers and brand, which in turn helps businesses to drive more sales and revenue.
Many DTC eCommerce brands are adopting this technique. If you've bought anything from Amazon, you may have encountered that it shows products you have previously purchased or related to them. That is because Amazon personalization is fully managed by Machine Learning, which records the user preferences, history, and purchasing behavior to tailor recommendations. This creates a flywheel effect that helps drive repeat engagement and loyalty over time.
In this game of personalization, DTC eCommerce brands are extensively using AI and Machine Learning to meet consumer expectations and personalization standards.
This strategy can contribute to your Direct-to-consumer organic marketing if you use your customer data accurately and precisely. Even a Salesforce report shows that companies that personalize their listing and offers in the right way drive 40% more revenue.
A mix of AI and Machine Learning models can help you achieve such numbers. How? Let's discover.
How can AI and Machine Learning improve direct-to-consumer marketing strategy?
Many small businesses still rely on guesswork to create a marketing strategy. This behavior makes them end up with low customer retention and less revenue. On the other hand, companies using a mix of AI and Machine learning seem to drive more sales and revenue.
Both AI and ML are great ways to improve direct-to-consumer strategy and customer experience based on customer data-driven feedback. A report shows that around 80% of marketers rely heavily on AI and ML to create customer journeys around their needs and brand objectives.
On one side, AI (Artificial Intelligence) plays a great role in solving the puzzle of "one size fits all" results. This technology helps marketers to understand the customer better and improve their experience. AI-powered marketing enables businesses to create a predictive customer analysis and build customer journeys more targeted and individually tailored.
Let’s consider a D2C business model example of elf Cosmetics. They use AI to show lighter lipstick shades for those who like them.
This D2C marketing strategy of adding recommendations helped them increase revenue per customer by 4.32%. And also, their "You May Love" section has garnered more than a 23% click-through-rate.
Let's look at another example - Nars, a cosmetic brand. It gives the best product recommendations based on the customer's previous history.
Nars uses AI to understand the customers' likes, affinities, interests, and preferences to showcase "RECOMMENDED FOR YOU." It helped them enhance market relevance and revenue by multiple folds.
Source: Freepik
AI not only helps you in personalization but also allows you to:
- Get actionable and beneficial insights from the marketing data.
- Increase accuracy and ROI on campaigns
- Shorten the sales cycle
- Reduce time spent on repetitive data-driven tasks
- Improve productivity and efficiency
On the other hand, Machine Learning adds more value to personalization. It allows businesses to eliminate the guesswork by automating data collection of customer behavior and speeding up the process of serving relevant content to the customer. Machine Learning is helping many retailers to expand their business. According to a Mckinsey report, US retailers have seen a 19% increase in operating margin over the last five years using data and analytics!
A brand like The North Face uses Machine Learning to know the customer preferences, history, and interests. When a customer contacts their virtual assistant, it will automatically advise the customer on the best products.
Benefits of using the power of AI and Machine Learning in marketing and personalization
Source: Unsplash
Your D2C growth strategy needs precision and knowledge of marketing trends and customer behavior. Relying on gut feeling can lead to a campaign misfire. Instead, incorporate AI and Machine Learning in your workflow to speed up your work and create campaigns that can work for your business. It will reduce the chances of human error and allow you to optimize your campaigns in a lucrative manner.
AI and ML collect the customer data and help you refine individual and most important data. The insights and data help you provide your customers with what they want, hence improving your customer experience. You can also use AI and ML to gather data from different channels to develop innovative ways to enhance customer engagement and spend wisely.
How can ML and A/B testing help you improve direct-to-consumer eCommerce business?
A/B testing has a lot of importance in the online world. Most marketers make their decision based on A/B testing. Why?
Well, it allows marketers to understand customer preferences. Usually, marketers segregate each campaign to determine which got a more positive response. However, this takes a lot of time, thus slowing down the marketing process.
By incorporating ML into your A/B testing, you can improve your efficiency. It allows you to test different campaigns and optimize older versions of campaigns as per the need. It lets you test more campaigns and collect information faster. With Machine Learning, you can track the customer's journey and tailor your campaign accordingly to provide your customers with what they like.
Examples of Brands using AI and ML to improve their customer service
Starbucks
Starbucks, a famous multinational coffee shop chain, leverages AL and ML to personalize their marketing campaigns and deliver an improved customer experience.
Nike
Nike, one of the most popular shoe brands, is also utilizing the combo of AI and Machine Learning to improve its marketing and product offerings.
Harley-Davidson
Harley-Davidson is an American motorcycle manufacturing company using patented algorithms that helps them get insights into predictive advertising effectiveness. Their proprietary techniques have helped them drive a 500% increase in ROI.
Nestle
Nestle, a Swiss multinational food and drinks processing company, uses AI, chatbots, and ML to personalize and deliver better service.
Integrate The Mix of AI and ML Into Your Business
Both AI and ML are great technology to cut out the time required for data collection and automate the workflow. These technologies automatically track your customers when they visit the site. AI and ML save this record and use it to learn the individual preferences and what they like or dislike on your site. When the same customer visits the site, your site will showcase what they liked earlier or related to that so that chances of conversion improve, and you can drive higher ROI.
Saffron Edge can help you incorporate AI and ML into your Direct to Consumer Marketing Strategy to keep a tab on your customer data, refine it for better recommendations, and create campaigns that convince customers to take action! Get in touch with us; we will walk you through our services and help improve your presence in the digital world. Contact us now!
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