How AI Can Influence Customer Decisions, Help Maximize Growth – CMSWire

September 13, 2022
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CMSWire's customer experience (CXM) channel gathers the latest news, advice and analysis about the evolving landscape of customer-first marketing, commerce and digital experience design.
If there was any benefit from the pandemic, it accelerated many organizations’ martech transformation efforts, changing the rules on how they manage customer relationships while exploring new technology solutions to alleviate the uncertainty the pandemic created.
Many of these changes have altered the marketing playbook forever affecting the way organizations approach personalization, content development, SEO, segmentation, campaigns, service and loyalty and retention.
The impact of these changes is significant. In a recent survey, half of the marketing leaders indicated that martech investments could drive revenue growth of up to 40% over next five years.
While this is a tremendous opportunity, the challenge many organizations still face is that their current marketing platform landscape remains fragmented, data sources are significantly disparate and current budgets don’t allow for massive transformation.
At the same time, the pandemic also increased customer sophistication and expectations as they did more buying and interacting online. Modern brands led the way for seamless online experiences, setting expectations very high. And a new entire segment of people who may not have interacted with a brand online, now were active online with your brand.
The result is that prospects and customers now expect value at every interaction they have with your brand. They are not afraid to switch products, vendors or end service agreements at the slightest sign of friction or complication in getting their goals achieved. In an experience-first world, you are not competing with your competitors, you are competing with the last great experience your customer had.
According to TechSee’s most recent survey results on customer loyalty, post-pandemic, there has been a significant increase in customers switching products or cancelling service reaching an all-time high of 43%. The survey highlighted that consumer loyalty is most impacted by poor quality customer experience with number one driver being broken cross-channel engagement flows.
Here are a few practical ideas you should consider to further your martech transformation.
The marketing technology, or martech, platform landscape continues to grow and remain fragmented making it difficult for organizations to consolidate and drive efficiencies. Over the past 10 years, marketing platforms have increased from around 150 to over 10,000 making it much harder for organizations to determine in which platforms to invest.
Industry consolidation has been difficult to achieve as the needs are vast spanning areas such as web content management, digital asset management, email automation, analytics and attribution, customer data platforms, journey orchestration engines, personalization engines and omni-channel content platforms. Vendors target a wide variety of capabilities, complexities and budgets to offer a full spectrum of choices.
The problem for buyers is that there is significant overlap in the platforms and tools and comparing these options can be costly and time consuming. Purchase decisions tend to center around specific use cases which drives siloed decision-making and platform fragmentation. Over 50% of marketers cite integration of disparate systems as the biggest obstacle to marketing success.
To avoid this, organizations must adopt an enterprise martech strategy to deliver a well-integrated, consistent technology stack to meet customer engagement goals. Workflow orchestration across platforms is crucial for business users to collaborate and enable multi-dimensional marketing campaigns. Data integration, collection and analysis are critical functions to ensure are operational across martech platforms. An inability to connect customer data assets will greatly limit the level of personalization and targeting that can occur with your target audience. 
The reality in many organizations is that it may not be practical to avoid siloed martech platforms, so at a minimum, you must build bridges between operational silos and organize the marketing team as multidisciplinary functions across the organization. To enable this, consider orienting the teams towards customer to infuse greater creativity, empathy and humanity in the way your marketing technology is utilized.
Related Article: 5 Insights Into the 9,932-Marketing Technology Landscape
Customer journeys continue to increase in complexity as they now transcend various channels and touch points as users continue to evolve how they interact with your brand. The path to purchase is no longer linear which makes offering personalized service and recommendations even more challenging.
Organizations need to think in terms of end-to-end customer journey orchestration and gather deep analytics at each point of the interactions. It’s critically important that you develop in-depth journey maps that consider all the different paths of interactions across multiple scenarios. This will also provide insights to the complexities and potential disconnects you may have during those journeys.
For instance, if a customer starts interacting with your brand on their mobile device, migrates to the website, interacts with a chatbot, fills an opt-in email form, adds items to a shopping cart, maybe calls into the service center and ultimately ends up in a physical store, all of these interaction points should collect information on intent, behavior and context. These are crucial for informing the next best action, offers or issue resolution.
Mapping customer journeys are a pre-requisite to understanding your customer's intent and helps inform a solid data foundation can be implemented with a CDP platform. Activating these insights is what ultimately will provide a richer customer experience and unleash new revenue opportunities.
Related Article: Expert Tips for Taming the Martech Madness
Platform fragmentation drives another critical requirement in the enterprise. As organizations now look across their martech and CRM platform stacks, they could easily have over 100 systems tracking and collecting customer data, with many of them not taking to each other.
This necessitates the need to have a unified customer data hub to feed a variety of downstream customer systems such as sales, digital commerce, customer service, advertising, point of sale and others. Providing a seamless, personalized customer experience regardless of the interaction channel is paramount to differentiating in the market.
These customer data platforms first emerged back in 2013 but have now advanced significantly to include artificial intelligence and machine learning capabilities to provide more predictive functionality in customer modeling, lookalike, segmentation and scoring. They have come a long way from just serving as a unified customer data repository.
CDPs have now become the platform on which organizations can begin to differentiate. Connecting data about your customers and prospects play a vital role in increasing advertising revenues, reducing content costs, attracting new customers, increasing subscription revenue and reducing churn.
There are several approaches for building a CDP. A fully integrated CDP platform (like an Adobe or Salesforce) provides a single, integrated platform that doesn’t require expensive integration across various product silos. A hybrid approach allows organizations to pick which components make the most sense to buy and where customizations will provide the most value. A fully customized CDP solution provided complete flexibility on the data pipeline and workflow management.
There is no one “right” approach for implementing a CDP.
It’s important to translate the data collected in the CDP into insights and actions to reach customers with the right experiences at the right moments.
One of the key aspects of delivering personalized experience is understanding the data and its context. Identity resolution is the process of consolidating user data across disparate sources and devices into a unified profile that tracks behaviors, interests, needs and other meaningful information about your customer.
The challenge in doing this arises as customers frequently interact with your brand through a variety of different devices — mobile, tablet, web, or point of sale — sometimes as an authenticated (or known user) and sometimes as an anonymous user (not known by user identification). Without a CDP, not all the data may be readily connected, and the quality of the data may be inadequate to make the appropriate connections.
Creating the proper identify resolution rules are critical to ensuring the right customer profiles are built. Deterministic matching, while conservative, is the safest way to ensure data integrity. Probabilistic matching is enticing as it allows you to build customer profiles without collecting any personally identifiable information (PII), but can lead to wasted paid media spend for your marketing team, and poor experiences for your customers.
Ideally brands need to develop their own first-party data and break the addition to third-party data and cookies. Embracing a deterministic approach as the core of your identity strategy will allow you to build high-quality customer profiles. Implementing the right identity resolution will enhance your segmentation, targeting, attribution, analytics, messaging, content and offers.
Related Article: What Is a Customer Data Platform (CDP)?
Once you have a unified data platform, you can gain even further competitive advantage by using artificial intelligence (AI) and machine learning to automatically surface customer insights. AI enables the analysis and interpretation of data much faster than human capabilities can handle due to the volume and veracity of the data. Algorithms continue to improve and are becoming self-learning which continues to improve outcomes.
AI is also being applied in many other areas of marketing. AI is helping power predictive workflows that can flag customer issues before service centers are even aware in platforms like Salesforce Service Cloud which now provides full digital contact centers for video, chat, voice and workforce engagement. AI is driving complicated real-time decisioning to provide relevant next-best actions as seen in platforms such as Pega Customer Decision Hub (CDH).
Conversational AI platforms like Botco.ai are enabling meaningful and intelligent conversations between businesses and their customers by providing 24/7 on-demand availability for businesses to ensure they don’t miss a single business inquiry during or outside of business hours.
AI is also beginning to play a bigger role in marketing content development. There are over 50 content generation platforms available with a wide variety of capabilities. Peppertype.ai generates content specifically for Twitter and LinkedIn articles and blogs. Wordhero can create over 50 types of content form blogs, social media posts, video titles, emails and many more. And NeuralText is an SEO tool that can automatically optimize content for better search engine results.
Of the companies recently surveyed by Pega, 30% have already adopted these fastevolving digital technologies like automation, artificial intelligence (AI), and machine learning. That percentage is expected to double to 60% in the next three to five years.
The use cases for leveraging AI in marketing are very diverse. The ability to automate repetitive tasks and quickly analyze large data sets to drive more insights are incredibly valuable. With marketing budgets under pressure, using AI technology can make these investments go much further. AI is unlikely to replace the human marketing touch, but is a very powerful tool to augment your current team and drive more meaningful results.
Marketing leaders are aware of what’s at stake. To drive growth through customer acquisition and retention, it’s critical for businesses to create a content-rich, frictionless and personalized customer experience. That’s hard to do given the complexity created by legacy systems, siloed technologies, underutilized data and changing customer expectations.
To address the need for more data-driven, personalized and effective marketing outcomes, businesses need to tap into the right skills, expertise, tools and accelerators to maximize existing investments and speed transformation. Tackling this level of complexity and creating the optimal experience require a unique set of skills, experience, tools and technologies — and that’s what leading enterprises are seeking.
The future looks bright. By applying best practices and pre-built and tested solutions, businesses are realizing the benefits of a successful martech transformation: Improved customer engagement, increased digital sales higher retention and reduced support costs.
Frank Palermo brings more than 22 years of experience in technology leadership across a wide variety of technical products and platforms. Frank has a wealth of experience in leading global teams in large scale, transformational application and product development programs.

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