Whether we realize it or not, artificial intelligence is already embedded into our daily routines. We ask Siri and Alexa to check the weather, order groceries, and look up the lyrics to our favorite childhood songs. We use Roombas with digital mapping to learn our apartment layout for efficient vacuuming. AI can even offer investing and health advice. A decade ago, AI was a novelty. Today, it has altered the fabric of our lives.
For customer-facing businesses, artificial intelligence offers similar transformational capabilities—from the way organizations communicate with their customers to the way they use customer data to continuously improve these experiences.
In this post, we’ll dive into three ways AI can benefit enterprise’s relationships with their customers.
How AI Benefits These 3 Key Areas of Business
AI pushes the boundaries of what companies can accomplish if they’re willing to reframe how they think of their data and their long-standing processes—here’s a peek at the change data science can bring.
1. Transforming Insights into Action
It isn’t enough for companies to gather data. At this point, it isn’t even enough to understand what the data tells them about customers. The real value of using AI is the opportunity to make faster decisions and act proactively. In this way, businesses can offer their customers real value before they ask for it.
For example:
- Starbucks began personalization efforts in 2016, and now they use AI to process data gathered from purchases to predict the offers that individual customers are more likely to resonate with. AI offers recommendations when customers approach physical stores and special offers during purchase processes.
- Unilever uses AI centers to uncover new trends for its brands—its subsidiary, ice cream brand Ben & Jerry’s, used artificial intelligence to discover a link between breakfast and ice cream. They launched a range of cereal-flavored ice creams based on AI’s link between social listening data along with CRM and traditional marketing research.
Artificial intelligence can unify traditional data resources with newer resources such as social media as well as transcripts or recordings from customer service interactions. Thanks to advances in processing, AI can handle a variety of what’s known as unstructured data—raw data humans create in our online interactions that don’t fit neatly into columns and rows.
2. Creating a Dynamic, Tailored Experience for Customers and Employees
Companies have always focused on creating excellent customer experiences, but artificial intelligence is improving employee experiences as well. Humans in the loop (HitL) use cases leverage AI alongside human expertise to optimize business processes. In this way, AI can integrate into your employee lineup and remove repetitive, manual tasks so that human workers can conduct higher-level work, such as building relationships, problem-solving, and innovating.
For example, a company might use an AI-powered chatbot to answer site visitors’ frequently asked questions. Many customers’ questions get asked over and over—such as, “What time do you open?” or “What is your return policy?”
Replacing a human worker with a chatbot has a variety of benefits:
- Chatbots answer questions 24/7 and in multiple languages. Customers can ask questions and receive answers across multiple channels, at any time of day in their preferred language. If a customer has a more complex need, they can tag a human representative to resolve the issue and, with automatic documentation, reduce the number of times customers need to explain themselves. Customers experience seamless, frictionless customer service—something many of them may not have thought possible.
- AI compiles relevant data from previous interactions so agents know the customer’s history, creating a seamless experience. They can successfully route emails, calls, and chats to the right place, reduce contact volumes, and virtually eliminate the simple customer service questions that tie up agents unnecessarily. Customer service agents can spend more time at high-touch stages with less manual effort required. Customers are happier and agents experience less stress.
3. Continuously Improving Performance
In the manufacturing sector, AI is helping reduce manual processes inherent across the supply chain. By automating documentation using data from purchase orders, shipment handoffs, and delivery notifications, organizations better understand where bottlenecks happen and can pivot without disruption.
- Walmart uses robotic process automation (RPA) to track inventory levels, identify slow-moving inventory, and improve which stock goes to which store to balance costs with reducing out-of-stock notices. It has improved inventory management over time despite its large size and complex partnerships along the supply chain.
- UPS uses an AI-powered logistics tool to plot the most efficient routes across its entire fleet. It reroutes drivers in real-time based on updated data from road and environmental conditions. The company predicts it will not only reduce late deliveries but can also reduce the overall impact its vehicles have on the environment by reducing the total number of miles traveled.
Over time, AI learns from data to improve its efficiency. It can schedule predictive maintenance before it detects a problem. It can flag inconsistencies in purchase fulfillments or notify all required parties of potential regulations violations. It can use historical and real-time data to understand customer patterns so that companies choose how much inventory to purchase, even in high or low-demand seasons.
Integrating AI into operational processes isn’t a one-time improvement the way it is when companies purchase any other tool—it uses past and real-time data to learn how to make the process better. Companies adopt a culture of continuous improvement as they interact with AI, and employees can spend less time on manual tasks to instead focus on problem-solving and innovation.
Start Transforming Your Business
Just as Starbucks suggests personalized offers and Ben & Jerry’s creates new flavors based on demand, AI adapts to a company’s unique needs over time. If organizations are willing to take on (and overcome) the challenge of an AI integration, they’ll be able to streamline their operations, make faster, more accurate decisions, and increase profitability.
To maximize their investments, enterprises need a comprehensive strategy for AI integration that incorporates the entire organization—from leadership down to operators on the shop floor.
In our Forrester-commissioned study, Accelerate Your Data-Driven Transformation, we break down how innovators across industries are using data science and machine learning for a competitive advantage. Request a copy of the report today!
