Next-best action 101: What it is, how it works & how AI can help

In today's business arena, having a stellar product or service is just table stakes. Your customers and prospects aren't just looking for solutions; they're craving experiences more personalized than their favorite barista knowing their complicated coffee order by heart. Enter the next-best action strategy: a data-driven approach to sales that acts as your secret superpower for anticipating prospect and customer needs that enables you to deliver tailored interactions that hit the mark every time.

Imagine having a secret superpower that allows you to understand your customers on a deeper level, uncovering their needs (maybe even ones they didn’t know they had) and serving up finely tailored experiences that make them feel like the VIPs they are. That's the essence of the next-best action approach: it's all about using data-driven insights to revamp how you make decisions, allowing you to infuse every aspect of your operations with smart, personalized solutions.

In this article, we’ll give you a high-level overview of what a “next-best action” strategy is, how it works, and how you can use it to significantly optimize your workflows. So, grab a coffee and let's dive in. 

By the end of this, you'll be a next-best action ninja, ready to take your customer engagement game to the next level.

What does “next-best action” mean?

Think of the next-best action as an informed, data-driven strategy that businesses like yours can use to figure out the best move in any interaction with a prospect or customer. It’s like knowing exactly the right thing to say at exactly the right time.

The next-best action strategy is based on thorough analyses of prospect and/or customer data (think: purchase history, preferences, intent data, etc), businesses can better understand their customers' behaviors and needs. Armed with these insights, go-to-market teams can then determine the best course of action to take with a given prospect or customer – whether that's offering a tempting deal, suggesting a complementary product, or simply reaching out with a friendly check-in.

"Next-best action" vs. "next-best offer": What's the difference?

While these two strategies are cousins in the personalization game, they have different ways of accomplishing that goal:

• Next-best action: The core idea here is identifying the most appropriate action to engage a customer or prospect that will help build long-term relationships with them. It's not just about making a sale (though that's always a nice bonus). Instead, the focus is on delivering a top-notch customer experience that keeps people coming back for more.
  
• Next-best offer: In contrast, next-best offer is a sales-centered strategy that’s laser-focused on one thing: closing that deal. It's all about analyzing prospect and/or customer data to figure out which kind of product or service they're most likely to bite on next. 

So, in a nutshell: 

• Next-best action = building lasting relationships through optimized sales experiences.
• Next-best offer = making a sale.

Both are valuable, but they're tackling different sides of the prospect and/or customer journey.

How does a next-best action strategy work?

Now, let's get into the nitty-gritty of how the next-best action strategy actually works. At its core, it's a data-driven approach that combines a few key elements:

1. Business rules: These are the guidelines that govern general sales and marketing practices or prospect/customer interactions.
2. Predictive models: Using fancy algorithms, these models attempt to forecast customer behavior and preferences. It's like having a crystal ball (but one powered by data, not mystical forces).
3. Decision arbitration: This is where the magic happens. Based on the business rules and predictive models, the system determines the optimal action to take for each customer scenario.

For example, let's say the predictive models suggest a customer is at risk of churning. The next-best action might be to serve up a tempting re-engagement offer. Or, if a customer just upgraded their plan, the system might recommend a friendly follow-up call to ensure a smooth transition.

It's all about using data to make smart, personalized decisions that keep your prospects and customers engaged and satisfied.

Here’s a deeper dive into the specific steps that go into determining a next-best action for a prospect or customer:

1. Crafting the perfect next-best action starts with data, data, and more data. The goal is to gather as much information as possible about a customer's interactions with your business. We're talking transaction records, website browsing behavior, customer service interactions, demographic info – you name it. 
2. Once you’ve collected the data, now you need to make sense of it all. That’s where innovative tech like analytics, AI, and machine learning systems come into play. They sift through the data to identify trends, recognize patterns, and understand behaviors. By considering factors like buying history, engagement with past promotions, and broader customer trends, businesses can gain a deep understanding of each individual's needs, preferences, and behaviors.
3. The final part of the process involves turning all of this acquired insight into the next-best action. This could be showcasing a personalized discount or other offer, suggesting a product that fits a predictable need they may have, sharing useful content, or even reaching out with a questionnaire or other feedback form for their input. 

At the end of the day, the next-best action strategy is all about using data to deliver experiences that are tailored to each prospect’s or customer's unique journey, ensuring they feel valued and understood at every touchpoint

What are the most common use cases for next-best action strategies?

The beauty of the next-best action strategy is its versatility. It can be applied across various industries, from sales and marketing to product development and customer service. Here’s how this could look within these different business contexts.

Sales

• Prospect discovery & engagement: Sales teams can leverage next-best action strategies to identify potential customers based on intent data and engagement patterns. Then, they can use that information to determine the right sequence and types of touchpoints that increase the likelihood of hooking the prospect.

Marketing

• Targeted campaigns: Marketing teams can use a next-best action strategy to tailor campaigns and communications with greater granularity and specificity. This enables them to target customers with relevant and timely messages that are written in a way that appeals to their unique needs. For instance, marketers might use next-best action models to identify the best time to send emails to each customer or use customer next-best action guidance to fine-tune personalized messaging.

Customer service

• Real-time support: Next-best action is widely used in customer service to support decision-making in real-time, providing suggestions to service reps on the most appropriate responses or steps to address customer inquiries, issues, or complaints. For example, if a customer has a history of delivery issues, the next-best action might involve offering a shipping upgrade or refund to resolve the issue.
• Cross-selling and upselling: Next-best actions can pinpoint add-on offers and recommended products based on a customer’s browsing and purchasing history, potentially upselling by suggesting items that complement what's already in the customer's cart.
• Customer retention: Salespeople can also use next-best action models to anticipate when customers might be losing interest and proactively make moves to re-engage them.

Product development

• Informing product updates & new features: Product development teams can use the next-best action strategy to identify what updates or new features might be most meaningful to customers.

At the end of the day, next-best action models act as a decision-making superpower, helping businesses deliver personalized, engaging experiences that drive customer satisfaction and business growth.

How does a next-best action strategy differ from a traditional campaign?

Traditional marketing and sales campaigns tend to be a bit... well, basic. They often rely on broad targeting,following a predefined plan based on market segmentations and general customer profiles. As a result, they serve up the same one-size-fits-all message to everyone who meets certain criteria.

Next-best action strategies, on the other hand, are all about personalization and adaptability. They capitalize on real-time customer data and continuously adapt to changing customer behaviors and interactions. Ultimately, this strategy allows you to deliver far more personalized experiences that anticipate each customer’s or prospect’s actual needs, preferences, and propensities.

While traditional campaigns are static and generalized, next-best action strategies are dynamic and tailored to each unique customer. It's like going from a megaphone to a private conversation – way more effective at grabbing attention and driving results. By continuously adapting to changing customer behaviors and interactions, next-best action strategies stay fresh and relevant, ensuring every interaction is optimized for maximum impact.

What are the benefits & challenges of using a next-best action strategy?

Implementing a next-best action strategy offers numerous advantages, from enhancing personalization to boosting sales. However, like any approach, it comes with its challenges. Here’s a detailed look at some key benefits and challenges to leveraging a next-best action strategy.

Benefits:

• Improved personalization: Next-best action strategies leverage customer data to provide tailored interactions, which can significantly enhance the customer experience.
• Increased customer engagement: By continuously adapting to customer behaviors and responding with relevant actions, next-best action strategies engage customers more effectively than traditional methods.
• Boosted sales: Next-best action strategies aim to pinpoint actions expected to increase conversions and ramp up sales with a nuanced understanding of information that bare-bones data analysis can’t supply.

Challenges:

• Data accuracy: The effectiveness of a next-best action strategy is heavily dependent on the accuracy and comprehensiveness of the data it uses. Predictive models may not accurately identify the most effective actions without complete and accurate data.
• Data privacy: Next-best action strategies require a significant amount of customer data, which creates an imperative for strict data privacy and security measures.
• Advanced analytics skills: Next-best action strategies often involve sophisticated analytics and machine learning techniques, which require specialized skills to implement, manage, and optimize these models.

Next-best action & machine learning: Unleashing AI's potential

Let's face it: the dynamic duo of next-best action strategies and AI is a match made in customer experience heaven. By integrating cutting-edge machine learning algorithms into your decision-making processes, you'll be able to predict customer behaviors with laser-like accuracy and craft strategies that hit the mark every time. It's like having a crystal ball, but way cooler (and more data-driven).

Incorporating AI into your next-best action strategy can be a complete game-changer – there’s no doubt about it. But as with any powerful tool, it comes with its own set of advantages and hurdles to consider. Let's break it down:

Benefits to consider:

• Predictive prowess: AI algorithms can crunch through vast amounts of data, predicting customer behavior and guiding your recommendations like a pro.
• Real-time adaptability: AI keeps your next-best action strategies fresh and dynamic, adjusting in real-time to ensure you're always making the most effective decisions.
• Scalability superpower: AI systems can handle massive volumes of data, allowing you to scale your next-best action strategies as your business grows without breaking a sweat.

Challenges to tackle:

• Data privacy concerns: With great data comes great responsibility. Ensuring strict data privacy and security measures is a must when dealing with such sensitive customer information.
• Data quality control: Garbage in, garbage out. Your AI is only as good as the data you feed it, so ensuring accuracy and completeness is crucial.
• Technical talent hunt: Implementing and optimizing next-best action models powered by AI often requires specialized skills in areas like advanced analytics and machine learning. Time to start hunting for your data whizzes!

At the end of the day, the combination of next-best action strategies and AI is a powerful force to be reckoned with. By embracing this dynamic duo, you'll be well on your way to delivering personalized, engaging experiences that keep your customers coming back for more.

Final thoughts

Next-best action strategies represent the future of intelligent, data-driven customer engagement. By leveraging AI and machine learning to analyze large datasets around customer behaviors, preferences, and journeys, businesses can determine the optimal action to take for every prospect and customer interaction.

Whether it's identifying the right outreach cadence for prospects re-engaging an at-risk customer, or cross-selling complementary products, next-best action provides a powerful capability to any go-to-market team. With predictive insights, you can deliver consistently personalized experiences that drive conversions, loyalty, and growth.

While implementing these strategies requires robust data practices and specialized analytical skills, the payoff is well worth it. Next-best action enables sales teams to operate with laser-focused efficiency, surgically improving every touchpoint of the customer experience. If you’re looking to gain an unmistakable competitive edge, embracing next-best action is an opportunity you can't afford to miss.