Analytics, data, and AI have the potential to enrich marketers’ understanding of their customers’ experiences in order to deliver meaningful, relevant experiences in the future.

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January 12, 2022
AI & Data Analytics: 3 Ways They Can Improve Customer
Experience And Engagement
process.st/ai-customer-experience
Leks Drakos
January 12, 2022
Artificial Intelligence, Customer Success
Since 2015, Nahla Davies has been working with enterprise clients around the world
developing RegTech protocols and best practices. She’s also worked with both enterprise
and sovereign governments as a key contributor for notable public projects like DCOM.
If the pandemic has shown the world anything, it’s that business professionals and,
specifically, marketers can still meaningfully engage customers in an increasingly digital
world. It’s undoubtedly challenging for marketers to continue providing a seamless customer
experience across different digital channels such as social media.
Thankfully, though, factors such as artificial intelligence (AI) and data analytics can make
multi-channel customer experiences engaging across the entire customer journey — from
product consideration all the way to purchase.

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Businesses have proven themselves both capable and willing to remain adaptable amidst the
tumultuous COVID pandemic in order to understand business problems and subsequent
opportunities. The process of actually understanding these problems and opportunities,
however, isn’t exactly straightforward.
Analytics, data, and artificial intelligence have the potential to enrich marketers’
understanding of their customers’ experiences in order to deliver meaningful, relevant
experiences in the future. To that end, let’s quickly take a look at how data and analytics can
be invaluable for marketers interested in enhancing the complete customer journey that they
provide across different digital channels.
Let’s jump in!
Tailored strategies enhance customer experiences
Marketers have the responsibility of considering an entire customer journey to better engage
customers along each step of the process.
This begins with the need phase – where a customer determines they have an issue that
needs solving — all the way through to purchasing, using, and even recommending a product
or service.

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The best way to determine how to improve the customer journey across each of these phases?
Creating a process of customer feedback analysis.
Customer feedback doesn’t just come from things such as a contact form — it comes from
everywhere, which can be both a blessing and a curse. A curse, in that it can be seemingly
impossible to scrape customer feedback from all of your business’s online presences; a
blessing, in that tools such as data analysis and AI can reliably aggregate all this customer
feedback into a digestible and comprehensive manner.

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Wide-scale aggregation of customer feedback is important to marketers who now need to
reassess the traditional hybrid approach of digital and physical customer engagement tactics.
It’s no longer an option to rely solely on leads generated from, say, in-person events and
solicit feedback from those events.
Marketers instead must think about how to best maximize their impact through digital
channels that make up their company’s global footprint. With innovations like machine
learning (ML) and AI, marketers can analyze massive sets of data with great accuracy to
understand which services customers value most across their customer experiences, such as
self-service tools like chatbots and virtual assistants.
The ability to analyze large sets of data is particularly important in a post-COVID business
world. B2B companies and their marketing teams have the opportunity to understand and
deliver on their globally-set priorities as well as develop a localized approach with teams of
regional and core domain experts that analyze historical campaign performance, develop
targeted segmentation, and incorporate analysis, testing, and insights.
As strategies to enhance customer experiences become more tailored based on the power of
data and analytics, companies must also use AI and ML to maintain personalized messaging
across their geographies and digital channels.
Analytics and data-driven personalization
AI and ML make it easier for businesses to connect with customers across multiple digital
channels to analyze customer data and turn them into actionable business intelligence.
Strategies to enhance the customer experience become clearer to develop and pursue once
businesses and their marketing teams study their sales cycle – from lead generation and
conversion to post-sales support – with the power of data and analytics.
Companies shouldn’t stop at just analyzing data, however: It’s important that they use AI-
augmented marketing to leverage their customers’ desire for personalization. After all,
customers almost always wish to be better understood and provide the value they’re looking
for based on their unique needs and wants.

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When considering what to achieve with AI-augmented marketing, companies can typically
start by using AI to create personalized product and service recommendations for customers.
AI and ML make it realistic for B2B companies to consistently personalize the
recommendations they display to customers which, in turn, drive traffic to more digital
channels and increase the rate of conversions of prospects who reach those channels.
Personalized recommendations can take many forms; popular examples include informative,
attention-grabbing ads that help customers understand why your products and services
address specific needs identified by analytics.

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Given the remote working environments in which many B2B companies are operating, it may
be wise to encourage collaboration between marketing teams and IT departments. Your
business’s developers and web designers may be able to further expedite the rate at which
you create a steady stream of new, personalized recommendations for customers.
After all, most developers started their career in a field other than development, so encourage
collaboration between your IT and marketing teams when possible. This collaboration should
focus on the automation of content creation and SEO for continuous and improved customer
interaction.
There’s no longer an excuse for businesses to lack a multi-channel presence through which
customers can connect with them. Fortunately, AI and ML now make it simpler than ever to
take advantage of remote working environments and coordinate department-wide efforts to
widen the available stream of personalized recommendations across these different channels.
Automation increases time for customer interaction
Tools that transform the customer experience with innovations like AI data not only help
marketers better recommend products and services to customers; they also help automate
content creation and search engine optimization (SEO) to generate keywords and automate
tedious processes like ad tagging so that marketers have more time to spend on face-to-face
customer interactions.
AI and ML efficiently create content generation and SEO automation tools with features
ranging from building blog posts to generating SEO keywords to automated ad tagging.
These tools let marketers focus more of their time on customer interactions rather than on
tedious, time-consuming background tasks.
However, privacy concerns may unsettle customers who are wary of data collection methods
AI and ML use to supply businesses with insight, efficiencies, and customization to their
customer experiences.
Marketers should be prepared to explain a bit more about data privacy and compliance with
customers as well as their business leaders should the topic arise during discussions about
AI-augmented customer experiences.
Businesses and their marketers must remind key business stakeholders as well as their
customers that PCI compliance is tantamount to the safe success of AI-driven marketing.
This protects personal and financial customer information from falling into the hands of
cybercriminals and keeps the ecosystem of digital payments secure.
Arguably the handiest aspect of AI-enabled chatbots is their ability to operate in conjunction
with each other. Chatbots, as well as any other autonomous customer experience service, can
quickly resolve issues such as transactional problems with their rapid information discovery

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capabilities. Some AI-enabled chatbots, for example, can use natural language processing to
quickly resolve simple questions that rely on complex data.
This information discovery extends beyond customer service inquiries; chatbots can even
analyze the unique history of a customer to provide personalized offers or advertisements
tailored specifically to the sales channel in which that customer is potentially buying. Rich
imagery, photos of product offerings, and even hyperlinks to product pages are all possible
pieces of personalized offers that AI can procure for interested customers.
AI and ML not only transform the way marketers and their businesses solicit customer data
and feedback; they make it feasible to automate the process of creating content that appeals
to customers, too. Automated content creation, as well as AI-accelerated SEO efforts that
generate keywords and automate tasks such as ad tagging, frees up time for marketers to
focus their full attention on the existing leads with whom they’re interacting.
This increased time that marketers can spend with customers becomes even greater when
businesses adopt AI-enabled chatbots, which are both useful to customers as well as
marketers with limited time on their hands.
Chatbots are becoming more useful than ever to customers
AI chatbots are finally coming of age as more businesses deploy AI-based chatbot
applications. More than 1,000 business leaders are now relying on AI-enabled chatbots with
which they can more closely follow the sales and marketing efforts of their business, and with
good reason: Although not a replacement for human contact and interaction, AI-enabled
chatbots and their interactions with businesses can provide an important balance between
self-service and face-to-face interaction with a real customer service representative.
AI chatbots are not only coming of age in a post-COVID landscape of largely remote business
operations — they are also the leading use of artificial intelligence among business leaders
and their companies. AI-enabled interactions with businesses, including chatbots as well as
virtual assistants and biometric-enabled readers and facial recognition scanners instill a
significant sense of trust in customers.
Not only do chatbots inspire confidence among customers, but they also inspire the same
feelings of satisfaction and trust among marketers who can rely on bots to perform lead
qualification and boost the efficiency and efficacy of their sales and marketing efforts.
Specifically, marketers can rely on AI-enabled chatbots because of certain advantages they
have over their human counterparts.
For one, chatbots can interact anytime and anywhere with customers — 24 hours a day, 365
days a year, all in real-time. Potential customers of a business don’t need to waste time filling
out and submitting inquiry forms, don’t need to wait for a response from a human customer

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service representative, and can expect instant, tailored advice regarding the products or
services they’re interested in.
This gives marketers the freedom to sit back and focus on existing leads while chatbots solicit
new prospects at the same time. Chatbots do a fantastic job of asking customers to rate their
experience and collecting suggestions on how to improve your sales process.

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The adoption of AI-enabled chatbots makes particular sense for businesses and their
marketing departments if they’re already deploying AI-based tools to assist with content
creation and mundane SEO tasks.
Chatbots take a large load off the hands of marketers who need to spend time conversing and
converting leads and who may not be able to analyze and collect customer feedback on their
experiences and impressions of advertising and marketing techniques.
AI & data analytics: The trend that keeps growing
AI and data analytics are rapidly changing and improving the ways with which businesses
and their marketers engage customers across multiple digital channels. Strategies to enhance
the customer experience begin with the analysis of large sets of customer feedback and data
pulled from different channels.
Wide-scale aggregation of customer feedback from these multiple channels allows marketers
to reassess their traditional hybrid approach of digital and physical customer engagement
with massive sets of data and improved insight into the services customers value most.
Analysis of such large sets of data is particularly important in the post-COVID business world
that demands B2B companies and their marketing teams to develop localized and global
approaches to analyzing historical marketing campaign performance, developing targeted
segmentation, and incorporating AI-enabled analysis, testing, and insight.
From there, marketers can use the data they’ve gathered to drive personalization with
consistent streams of targeted advertisements. AI and ML let marketers spend more quality
time with customers — just be careful to remind your business leaders as well as your
customers that measures such as PCI compliance are in place to safeguard personal and
financial data that your AI-augmented campaigns gather.
Finally, businesses should consider adopting AI-enabled chatbots, which are becoming more
useful than ever to both customers as well as marketers. AI-enabled chatbots provide a
crucial balance between automated self-service as well as face-to-face, human interaction
provided by real customer service representatives. These chatbots remain the leading use of
artificial intelligence among the majority of business leaders due to their ability to inspire
confidence and trust among customers.