Marketers can now use data like never before: it not only gives insight into the target audience but also enables marketers to create a better user experience and deliver the instant customer service that today’s consumers demand.
Instant customer service through AI and other marketing intelligence can help brands drive conversions and build loyalty. Customers are much more likely to interact with a brand that responds quickly, even if it costs more or has other caveats, such as selection or location.
For instance, this 2018 research by PwC found that 65 percent of U.S. consumers believe positive customer experience is more influential than advertising. While the study also showed that 75 percent want more human interaction, marketing intelligence allows brands to use a combination of strategies to roll out AI and human-based customer service that can help as many customers as possible in the way they prefer.
Without a positive customer experience, all other marketing strategies fall on deaf ears. Using marketing intelligence to better capture the customer’s path to purchase can help marketers learn what the audience is expecting and how to enhance the buyer's journey.
Better still, accurate data that leads to more focused customer experiences generates higher customer loyalty, reduces paid campaign costs (due to a narrower, more specific audience), and creates better retention rates through custom messaging.
In addition to better sales and word-of-mouth recommendations, happy customers lead to greater market saturation and give organizations the ability to grow and establish credibility in their industry. By constantly evaluating customer experience data, marketers are focusing on the end first, which allows them to work backward to determine what could be improved or included for a better user reality.
Customer analytics in relation to marketing has a lot of benefits to both the customer and the organization. A Forbes article reports that over half (58 percent) of businesses are seeing an increase in customer retention and loyalty because they use customer analytics. A big part of this is due to the fact that customer analytics and data can be used to personalize the experience for the customer, which increases the likelihood they’ll not only buy again but that they purchase in the first place.
The premier example of personalized marketing at scale in an ecommerce setting is Amazon. As users continue to interact with the ecommerce giant, the recommendations on various pages throughout the site get more specific. Amazon also begins to alert customers of new product releases of interest, as well as email lists or giveaways that tie into the customer's favorite categories.
A better experience driven by marketing intelligence has become one of the most valued sales and marketing strategies for many organizations, a recent article by Mckinsey shows. Those polled said they value the use of customer analytics over digital marketing, channel management and advertising management when it comes to the success of their company.
When it comes to online experiences, consumers have vastly heightened expectations. They expect a level of personalization to cut through all the clutter of companies competing for their time, attention and spend. This is why it is crucial for marketers to learn more about customers through available marketing intelligence methods to personalize e-audience experiences.
Today, marketers are leveraging a variety of measurement models and developing technologies to better understand their consumers. These include:
As CMO.com reports, artificial intelligence will help the humans behind brands, not replace them. Chatbots are a perfect example of how AI is helping marketers reply to more customers faster, giving them more time and resources to personally help customers who have advanced needs.
For instance, if a customer needs a return label, a chatbot is likely able to do this on its own without human intervention. Additionally, the use of AI in this instance does not bother the customer, as their end goal is to get a return label and get a refund for an item.
However, if someone has a more nuanced request, such as a hotel room request for a disabled person, human interaction is crucial, as it may involve more than a black and white response. By freeing up human customer service resources using AI for basic requests, companies are able to assist the more sensitive customers at a time when having a personalized experience with another human is key to long-term retention as well as recommendations.
Automated experiences with AI can give marketers valuable insight into what customers are looking for and how these needs change depending on the medium of engagement. For instance, a person interacting with an AI chatbot is likely to ask for different things than one filling out an email or calling the customer service department. These nuanced differences lead to more advanced data that can be analyzed to help organizations provide an even better customer experience.
As marketing continues to evolve, organizations are realizing a need for better data reporting that encapsulates all online and offline marketing campaigns and activities. While specific data about each strategy is key to understanding that part of marketing, unified marketing measurement (UMM) is a good way to get a holistic view of how all marketing performs through one analytics datapoint. UMM aggregates and normalizes data from across devices, campaigns and touchpoints for a look at person-level interactions and high-level trends to demonstrate how these worked together to influence the buyer’s journey.
UMM is a good way for marketers to distill progress and results to the executive team. Even more vital, UMM allows marketers to analyze cross-campaign data, determine actionable insights and next steps, and continue meeting or exceeding company goals.
Timely insights involve predicting a customer’s behavior or response to a specific action taken via customer service or during the engagement process.
An important use of right-time insights in marketing is to course correct campaigns based on how consumers are reacting to or engaging with the ads. For this, marketing teams require a marketing analytics software that can process the data gleaned from campaigns quickly, as they are being run.
For example, let's say a marketing team is running a campaign on Instagram with native content, however it is not yielding engagements from their target audience. Historically, marketers would not know that engagements were down until the end of the campaign, meaning they were wasting money on content that did not convert. Right-time marketing intelligence, however, would alert marketers to the underperformance of this campaign, and show them that they were not using creative that resonates with their target demographic. Getting this information in real-time allows them to update the campaign while it runs, achieving better ROI.
These timely, actionable insights can also be deployed through customer service employees directly. If a customer calls to cancel their subscription, insights can help a customer service representative determine what type of offer would most entice them to stay. For instance, if the data shows that this customer has subscribed to the NFL game TV package in the past, offering it to them again for a discount could cause them to stay longer, thus increasing company revenue in the long run.
Right-time insights also encapsulate live data collected through social media. By using social listening and reputation monitoring to determine what a target audience is talking about can help marketers understand their needs and respond to them accordingly.
As data and marketing intelligence becomes smarter and more specific to customer needs and expectations, marketers are better able to craft campaigns, content and a better customer service experience. This leads to better engagement, lower return rates and higher conversions. At the same time, by making customers feel more heard and valued, brands are strengthening trust and loyalty.
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