The eCommerce industry has exploded. In fact, eCommerce is expected to reach $7.4 trillion by 2025, with a compound annual growth rate of 12%. So, as an emerging direct-to-consumer (DTC) brand, you must constantly look for technologies that can streamline your operations and give your company a competitive edge.
That’s why many brands have turned to machine learning and artificial intelligence. By using these innovative technologies in marketing, you can build more impactful campaigns, personalize your marketing materials, and save yourself time and energy in the process.
While machine learning and artificial intelligence may seem like far-fetched concepts above your pay grade, they can be very useful tools for DTC brands and marketers. In this blog, we’ll discuss machine learning and artificial intelligence, how these technologies can optimize marketing efforts, and how personalization and data analytics integrate with these technologies to elevate marketing strategies.
What are Machine Learning and Artificial intelligence?
For years, machine learning (ML) and artificial intelligence (AI) have seemed like improbable ideas that would never become a reality. But today, ML and AI play an active role in various industries, especially eCommerce marketing.
ML and AI are often used interchangeably but refer to different aspects of modern technology. AI is a broader concept that refers to a set of technologies designed to perform tasks usually requiring human intelligence, such as problem-solving, understanding natural language, and recognizing patterns. Some examples of artificial intelligence technologies you likely use daily include voice assistants, chatbots, facial recognition, Google Maps, and text editors like Grammarly. AI is everywhere!
On the other hand, machine learning is a subset of AI that focuses on developing algorithms and statistical models that enable computers to learn from and make predictions based on data. ML aims to teach a machine how to perform a specific task and provide results by identifying patterns and analyzing data.
In marketing, ML and AI can analyze vast amounts of data to uncover insights and patterns that human marketers might miss. This ability to process and learn from data at scale makes these technologies particularly valuable for creating personalized marketing campaigns.
5 Ways ML and AI Technologies Are Optimizing DTC Marketing Efforts
This innovative technology is exciting, but how exactly can machine learning and artificial intelligence be used in DTC marketing efforts? ML and AI can be used in various ways to enhance marketing campaigns—so much so that 61.4% of marketers have already used AI in their marketing activities. Here are 5 key applications for AI and ML in DTC marketing:
1. Customer insights and segmentation
ML algorithms can analyze customer data to identify distinct segments within your customer base based on purchasing behavior, browsing habits, demographic information, etc. This allows DTC brands to tailor their messages to specific groups, increasing relevance, engagement, and conversion rate.
Let’s take demographic segmentation, for example. DTC brands can leverage ML technologies to split their audience and create more in-depth customer personas based on age, gender, income, level of education, job roles, and more. By segmenting your audience based on your customers’ income, you can target customer sets with products that fit their budgetary needs.
2. Predictive Analytics
By analyzing historical data, ML models and AI can predict future customer behavior, patterns, and trends. This can help marketers anticipate customer needs and preferences, enabling them to deliver the right message at the right time. Predictive analytics can help your brand answer critical questions like:
- How do your customers like to interact with brands?
- What products are your customers currently searching for?
Leveraging predictive analytics empowers DTC brands to tailor their products, services, and campaigns accordingly to meet their customers’ changing needs and acquire new customers.
3. Personalization
According to Accenture, 91% of consumers are more likely to shop with brands that remember them and send them relevant offers. For growing businesses, that means personalization is not an option—it’s an essential part of growing a business, whether that business sells purely online, in-store, or in a hybrid setting. This highlights the growing significance of personalized advertising in today’s fiercely competitive marketplace.
AI-powered recommendation engines can suggest products or content that individual customers will likely be interested in based on their past behavior and preferences. For example, if a customer purchases a pair of sneakers, a recommendation engine may showcase an article on how to care for the sneakers or a pair of socks to go with them. This personalization can significantly enhance the customer experience and drive sales.
4. Product development
Artificial intelligence and machine learning technologies can quickly analyze market trends, interpret customer feedback, and extract insights from competitors to identify consumer needs and preferences. What features are your customers talking about the most? Do your customers have particular needs or emotions regarding certain product features? AI can convert this feedback into quantitative data so you can adjust your products to meet future demand.
5. Proactive customer support
One primary goal of DTC brands is to make the customer experience as seamless and efficient as possible. Customers who come to your brand with questions or concerns want an answer immediately. Not by the end of the day or next week, but right now. That’s where chatbots come into play.
AI-driven chatbots can provide personalized interactions with customers, answering queries, providing product recommendations, and assisting with purchases promptly. The chatbots are programmed to anticipate customer questions based on historical data to provide proactive and helpful support. This improves customer satisfaction and frees up human resources for more complex tasks.
Why Should Your DTC brand consider using ML and AI?
The value of ML and AI cannot be understated. According to the Global Artificial Intelligence Study from PwC, AI is expected to contribute $15.7 trillion to the global economy by 2030. Aside from the rich insights that these technologies provide DTC marketers, there are 3 main reasons why your business should consider implementing ML and AI into your marketing strategy:
1. Decreased costs: Despite popular belief, machine learning solutions and artificial technologies aren’t hundreds of thousands of dollars. These tools are often already built into your existing marketing tools, like your CRM or email marketing software. In addition to being affordable, these tools can help cut down on operational costs.
2. Saves time: The biggest benefit of machine learning is its ability to quickly and accurately analyze significant data sets. Manually conducting data analysis can be extremely monotonous and time-consuming. What takes a human hours, days, or weeks to do can often be done in seconds with machine learning software. Now, your team can spend more time on tasks that directly impact your brand’s performance and leave the repetitive tasks for the technology to handle.
3. Increased revenue: 41% of businesses worldwide have seen increased revenue growth using artificial intelligence in marketing campaigns. Because DTC brands can utilize higher-quality data to inform campaigns, personalize marketing messaging, and automate processes that would otherwise take extensive amounts of time, increased ROI can largely be attributed to AI and ML.
Two DTC Brands That Are Crushing It With AI
Several brands have successfully leveraged AI and ML to create personalized marketing campaigns that drive foot traffic, increase conversions, and boost customer acquisition rates.
Sephora, for example, utilizes AI-powered chatbots and virtual assistants to provide personalized beauty recommendations to its customers. This has enhanced the in-store experience and encouraged customers to visit its physical locations. Sephora has also integrated “color IQ” software that analyzes a customer’s skin color, texture, and skin type to offer personalized product recommendations.
Wine Insiders has also jumped on the AI bandwagon. Wine Insiders taps into Nift’s proprietary AI to gain exclusive access to consumers who are actively engaged with our consumer app partners. Nift’s patented AI finds incremental new customers most likely to deliver the right LTV, which has resulted in Wine Insiders driving 151% in new customer acquisition and averaging a 10% new customer conversion rate.
The Importance of Tailor Marketing Messages & How Data Can Help
The right data allows DTC brands to tailor marketing messages to individual preferences. DTC marketers can gain a deeper understanding of their audience by collecting and analyzing data from various sources, such as customer interactions, social media activity, trends, and purchase history. This insight allows them to create highly targeted campaigns that resonate with individual customers.
For example, a DTC brand can use data analytics to identify which products are most popular among certain customer segments. They can then craft personalized email campaigns highlighting these products, increasing the likelihood of conversion.
Additionally, data analytics can help DTC marketers track the effectiveness of their campaigns—because sometimes you just can’t get it right on the first try. Data allows for the continuous improvement and optimization of marketing campaigns and messaging.
Data, artificial intelligence, machine learning, and human brainpower can create emails, ads, and other marketing content that speaks directly to customers’ interests and needs.
The Perfect Mix: AI, Personalization, and Gifting
At Nift, we’re all about utilizing artificial intelligence to create hyper-personalized marketing campaigns. Our platform uses AI to help DTC brands acquire net-new customers outside of paid search and social media by simply saying ‘thank you’. Learn more about our process and request a demo to see how Nift has 100% clear attribution tracking for Shopify sites.
About the Author
Cynthia LaRue is the Vice President of Marketing at Nift, where she develops an integrated sales and marketing growth strategy to elevate the Nift brand, foster customer awareness, and drive brand preference across various marketing channels.
Cynthia’s passion lies in leveraging digital platforms to connect with customers innovatively, driving demand for Nift. Collaborating closely with the Sales Team, she spearheads efforts to transform capabilities and stay ahead in the ever-evolving e-commerce industry. Her commitment to fostering diverse and engaged teams is at the core of her approach.
Throughout her career, Cynthia has navigated both scrappy startups and global enterprises. Before joining Nift, she served as the Head of Marketing for ShipStation. Her impressive track record includes pivotal roles at Fortune 500 organizations such as The Home Depot and Mars, where she focused on digital e-commerce and held P&L responsibilities for the M&M’s brand.
Outside of work, Cynthia resides in the greater Houston, TX, area with her husband. She indulges her creativity by designing jewelry, exploring hiking trails, kayaking, swimming, and writing. Cynthia holds a dual degree in management and an MBA from Belhaven University, where she graduated Summa Cum Laude.
