Skip to content

The Importance of Knowing Your Customer: How Personal Touches Drive Buying Decisions

  • 9 min read

In today’s ultra-competitive marketplace, personalization is the magic ingredient to boost retention and growth. In real-life scenarios personalization can be as simple as remembering a name or chatting in a friendly, human tone. Satisfying the basic human need for connection builds trust and makes customers feel like they truly matter. It’s in these moments we transform transactions into relationships and customers into fans.

By Simon Harrison
Analyst and Client Executive Partner

Simon is an industry analyst who has authored over 30 Gartner Magic Quadrant notes as lead and with colleagues. He’s written important research as the Chief of Research advisor for Gartner. He continues to provide deep research and insights as an Executive Partner for Actionary clients and the industry..

I recently walked into a car dealership I hadn’t visited in seven years and was greeted by the sales associate who’d remembered my name and even the last conversation we’d had, back in 2017. I couldn’t believe it, I was so impressed. What surprised me about myself was I then decided I really wanted to buy a car from this guy. And it didn’t stop there, I wanted to buy a couple of company cars for myself and our co-founder, too. So, what’s going on here? Why did just remembering my name after all these years invoke a sense of loyalty to this particular dealership?

The Psychological Impact of Recognition

Recognizing a customer by name or recalling anything from a previous interaction significantly affects buying psychology. It makes the customer feel valued and respected, which is a powerful motivator for loyalty and purchasing. McKinsey completed a study on how behavioral psychology can significantly enhance customer experience and sure enough, providing customers with a sense of control, ensuring positive closing experiences, and acknowledging individual preferences is proven to boost customer satisfaction dramatically. Businesses that treat customers as individuals and foster a human touch help them feel seen and understood, thereby strengthening emotional connections. These connections turn into long-term relationships and increase customer lifetime value. So, how do we achieve this digitally? Is it even possible?

Real-World Personalization Success using AI

I recently attended AWS Summit 2024 in London, along with more than 32,000 people who came to the event — the queue for coffee was unbelievably long — and one particular presentation stood out to me, provided by Selfridges, a popular UK department store. The company decided to use Amazon Personalize, a service that leverages user data to personalize communications and offerings. They augmented this with Amazon Bedrock’s generative AI foundation models (FMs) to create targeted recommendations and sophisticated search experiences. Amazon claims it can be used to detect market trends, generate recommendations in a company’s brand, and help customers find more relevant items quicker. Selfridges put it to the test and measured online performance in two key ways — clickthrough rate and add to bag. The results were staggering and real. Using Generative AI to make things more personal caused an uplift of 130% in clickthrough rates and adding to bag went up by 270%! This is nuts but REAL.

Generative AI can make searching and buying a product feel like you’re engaging in a one-on-one human relationship type interaction? How is that possible? Regardless, it’s happening and businesses can really foster long-lasting brand loyalty using clever technology. So, what other technologies can help?

Achieving the Utopian Personalization Solution

Offering seamless, hyper-personalized journeys that start before a customer even contacts an agent and continues long after a transaction is complete requires a seamlessly connected ecosystem of apps:

  1. Live engagement platforms that leverage AI to offer agents real-time insights based on customer data.
  2. Live and predictive analytics that monitor these interactions, analyzing customer sentiment and feedback to refine and improve the overall experience.
  3. Always-On personalization that continuously learns from customer behavior to offer targeted content and recommendations that feel uniquely tailored to each user during online experiences.

Businesses that consider a holistic personalization strategy that combines the benefits of these technologies dominate the customer experience landscape.

Personalizing Live Engagement

When it comes to live engagement there’s several key technologies that edge out in helping businesses to understand and interact with their customers better. These apps help turn data into actionable insights and personalized customer experiences.

1. Customer Relationship Management (CRM) Applications

CRM applications such as Freshworks, Salesforce, Zendesk and Zoho empower businesses to fine-tune their marketing, sales, and customer service strategies by capturing detailed customer preferences. These platforms are increasingly facilitating direct connections with customers, particularly through digital channels, similarly to contact center applications, too.

What’s important to note is that everything about why a customer responded to a marketing event, the information to support the sales team in nurturing a lead and the insights to make each customer interaction more relevant and effective is stored in the CRM application. Then, once onboarded, that same data as well as information on the customers’ evolving needs can be used to make experiences more personal. CRM applications are designed to understand a customer’s lifetime value journey more holistically and this is a big deal in customer acquisition, retention and loyalty.

2. Contact Center as a Service (CCaaS)

CCaaS vendors like Five9, Genesys, NICE and Talkdesk are transforming the way businesses engage with customers across the entire customer lifecycle, too. These platforms don’t tend to store the customer data but they do capture engagement data which is hugely important for making things personal. Combined with close CRM application integration CCaaS apps are an essential platform for making customers feel valued.

More important, still, CCaaS vendors provide the voice connectivity that CRM application providers rely on and personalization is a crucial aspect of connecting live, too. For example, through sophisticated AI and machine learning technologies, CCaaS platforms like Five9 and Talkdesk analyze customer data in real-time to provide agents with actionable insights, right there and then. Agents can understand context, predict customer needs, and personalize the communication live.

Automated callbacks, scheduled follow-ups, and proactive notifications based on customer behavior and preferences are all benefits of a CCaaS application. Boosting customer connection like this enables better anticipation of their needs, and the ability to address potential issues before they arise — making the relationship feel more personal.

3. Digital Customer Service Solutions (DCS)

DCS solutions like Gladly and Glia enable real-time digital communication options such as video, voice, and co-browsing to be more engaging. Agents guiding customers through complex processes in real time, personalizing the support experience and building stronger, more personal, relationships is the goal here.

DCS solutions target proactive engagement, too, where businesses can initiate contact with customers based on predictive insights. For instance, if a customer is repeatedly visiting the help page or a specific product page, the service can prompt a live agent to reach out and offer assistance or additional information, thus anticipating the customer’s needs before they even make contact.

Analytics-Powered Personalization

1. Live Analytics Solutions

Vendors like Verint and CallMiner are driving deep personalization through advanced speech analytics. Verint has shifted its strategy, now focusing on AI-powered CX automation — leveraging AI to enhance real-time customer interactions. Verint’s suite includes tools like Coaching Bots, which provide in-the-moment guidance to customer service agents, allowing them to tailor their approach based on customer emotions detected in real-time. These insights empower agents to address customer needs with a personalized touch, fostering loyalty and improving satisfaction.

CallMiner’s Eureka platform provides the ability to analyze not just spoken interactions but also cross-channel communications, extracting emotional cues and key insights, again, in real-time. By interpreting customer sentiment and providing actionable data mid-conversation, CallMiner allows businesses to personalize responses instantly, addressing frustrations or satisfaction as they occur. This combination of real-time emotional intelligence and predictive guidance transforms standard conversations into highly personalized experiences.

2. Predictive Analytics

Apps like Pega, SAS, and IBM Predictive Analytics offer pre-emptive capabilities, anticipating customer need and equipping staff to provide deep personalization experiences.

Pega excels at predicting customer behavior by leveraging historical data and real-time insights — businesses can anticipate needs and proactively deliver tailored personalization experiences. SAS takes predictive analytics further by applying advanced machine learning models to large data sets, providing businesses with actionable insights into customer preferences and potential future actions. Whether it’s predicting a customer’s next purchase or anticipating churn, SAS enables organizations to deliver the right message at the right time, driving deeper engagement and long-term loyalty.

IBM Predictive Analytics offers similar predictive capabilities, using AI to forecast customer behavior and segment audiences for hyper-targeted engagement strategies. Its AI tools help businesses adjust their approach dynamically, ensuring each customer interaction is as personalized as possible.

Always-On Personalization

Amazon Personalize stands out in e-commerce and digital-first platforms, continuously learning from customer behavior to recommend highly relevant products and content.

By integrating Google Cloud Recommendations AI, businesses can tailor content and product recommendations in real-time, based on user preferences and behaviors. Azure Personalizer provides adaptive content recommendations by leveraging reinforcement learning to continuously improve user experiences.

Finally, MorphL AI specializes in e-commerce personalization, offering real-time predictions about user behavior to drive marketing efforts and optimize shopping experiences

Conclusion

There are many different applications that can support deeper personalization goals. In an era where customer expectations are at their highest, vendors that are already thinking about more comprehensive and deeply personalized experiences at every stage of the customer journey are better technology partners.

Predicting customer needs, offering tailored content and improving live engagement personalization starts to build back into this digital era the kind of experiences that cause buyers be more loyal to a brand, again.