With the astounding success of ChatGPT in recent months, more companies are looking for ways to make AI and big data work for their organization. But while there are hundreds of articles on the benefits of AI and big data, few give you a good idea of how it should work and how you can successfully deploy it.
So instead of reading another post on how AI and big data change our lives, let’s focus on specifics — what exactly you can do to deliver more personalized experiences for customers (so you can increase your sales)? In this article, you’ll get a how-to guide on implementing AI in your company from a business perspective.
How to use AI and Big Data for individualized customer journeys
Let’s outline the areas you should focus on when planning your strategy for personalizing your web content for higher sales.
1. Start with data collection
To create individualized customer journeys, businesses need to collect data on their customers. This includes both demographic data and behavioral data, such as purchase history, website clicks and social media interactions.
The data collection process is one of a few integral elements of AI models, which include the following workflow:
Next, you must sync your data — usually stored in a warehouse — with third-party tools such as Salesforce or Hubspot. Operational analytics lets you use these tools better and reach your consumers at the right time at scale.
But let’s get straight to the point — how can you use it? Check out these ideas for using AI and big data for individualized customer journeys:
- Personalized recommendations: When you know more about your customers’ choices, you can offer products they want to buy. For example, if a customer frequently buys running shoes from your store, you can recommend similar products or accessories related to running.
- Targeted email campaigns: Instead of sending one generic email to the whole email base, segment your marketing campaigns. Personalize emails and add targeted offers so you resonate with different customer segments better. In this process, you should comply with all applicable regulations on handling personal information and ensure data security practices are in place.
- Targeted PPC campaigns: You can easily spot trends by collecting information on user website behavior. You can then segment users and retarget them with personalized ads on Facebook or Google. For example, you can show users a new swimwear collection in your ads if users visit the swimwear category.
- Use dynamic website content: Using data to personalize website experiences can improve engagement and conversions. For example, if a customer has previously purchased a particular product from your website, you can highlight related products on their next visit.
2. Use predictive analytics
Predictive analytics is one of the five types of analytics — including descriptive, real-time, diagnostic and prescriptive analytics. Predictive analytics looks at what might happen in the future based on past results.
Predictive analytics involves using data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.
By analyzing historical customer data, you can anticipate future customer needs. For example, if a customer frequently purchases a certain type of product, predictive analytics can anticipate when they will need to purchase that product again and remind them to do so.
There’s also another application — identification of user preferences and behaviors. This information can be used to create personalized marketing messages, recommend products, and tailor customer experiences.
Handling a large amount of data while deploying your models requires reliable cloud hosting — you can consider the private and hybrid cloud or even dedicated hosting. Private clouds add a layer of security and even have custom replication clusters that will reduce downtime. Hybrid cloud hosting lets you deploy a private cloud to protect sensitive data and use public hosting for less critical tasks.
3. Implement chatbots
Chatbots are automated systems that can interact with customers in real-time, providing them with personalized assistance and support. Using chatbots, businesses can offer customers a more customized experience and respond to their inquiries and concerns quickly and efficiently.
They achieve it by analyzing customer data to provide personalized recommendations and advice. For example, if a customer is looking for a product, the chatbot can recommend related products based on their browsing and purchase history.
4. Leverage social media
Social media provides businesses with a wealth of customer data, including their interests, preferences and behaviors. By analyzing this data, you can create personalized experiences for your customers and engage with them on a more personal level.
What does it look like in practice? First, it shouldn’t be as complicated (as it sounds!). So check out these applications of AI and big data you can put into action using third-party SaaS tools (no coding required):
- Analyze social media data: Businesses can gain insights into their customers' interests and behaviors by analyzing social media data. This data can be used to create personalized marketing messages, develop targeted advertising campaigns, and optimize the customer journey.
- Engage with customers: Social media provides businesses with a direct line of communication. By engaging with customers on social media, companies can build relationships and gain valuable feedback on the customer journey.
- Personalize customer experience: You can use social media data to recommend products or services based on customers' interests and preferences.
- Monitor brand sentiment: Social media provides businesses a platform to monitor brand sentiment and respond to customer feedback in real time. By monitoring social media conversations, you can identify areas for improvement and make necessary adjustments to the customer journey.
- Use social listening tools: Social listening tools monitor social media conversations and identify trends and patterns in customer behavior. These insights can be used to create more effective marketing campaigns and optimize the customer journey.
5. Personalize marketing messages
Marketing messages should be tailored to each customer's unique needs and preferences. By using data analysis and segmentation techniques, businesses can create personalized marketing messages that resonate with their customers and drive engagement.
Brian Lim, CEO of iHeartRaves & INTO THE AM says:
6. Continuously measure and optimize
Creating individualized customer journeys is an ongoing process that requires continuous measurement and optimization. By tracking customer behavior and feedback, you can identify areas for improvement and make necessary adjustments to capitalize on your customer experience.
Here are some ways you can measure and optimize individualized customer journeys:
- Monitor customer behavior: By monitoring customer behavior, you can identify pain points in the customer journey and make necessary adjustments. This can be done by tracking metrics such as website traffic, click-through rates, and conversion rates.
- Collect customer feedback: Customer feedback is a valuable source of information for businesses to improve their customer journey. Feedback can be collected through surveys, social media or customer service interactions. You can use it to identify areas for improvement and adjust the customer journey accordingly.
- Test and iterate: You can use A/B testing to test different versions of your customer journey and analyze the results. This allows you to identify which changes are most effective and make continuous improvements over time.
- Use customer journey mapping: Customer journey mapping is a tool that can help businesses visualize the customer journey. By mapping out each step of the customer journey, businesses can see the journey from the customer's perspective and identify pain points that need to be addressed.
AI and big data provide businesses with powerful tools for creating individualized customer journeys. By collecting and analyzing data, implementing chatbots, leveraging social media, personalizing marketing messages and continuously measuring and optimizing, you can create tailored experiences that resonate with your customers and drive engagement.