Blogs Gen AI and the changing landscape of customer relationship management

Gen AI and the changing landscape of customer relationship management

25 April 2024
Gen AI and the changing landscape of customer relationship management

‘‘The purpose of a business is to create and keep a customer’’, Peter Drucker, a famous writer, and management consultant.

Every business, lives, profits and grows with this mantra. Business that succeeded across all the previous industrial revolutions including mechanisation, electrification, automated production, and computation have one common trait. Each of this business not only changed consumer lives but also the experience of interaction with the business and utilisation of its product or service. So, what changes today, in the 4th industrial revolution that was set off by the advances in computing and information and communication technology and is built on 4IRs. Firstly, connectivity, data and computational power, second - analytics and intelligence, third human–machine interaction and fourth - advanced engineering. These form the 4 pillars of Industry 4.0. Technology, is only half of what businesses have to adopt and change. Two additional major factors that change the business environment are, customer demographics and behaviours and introduction of new business models.

Marketing and sales strategies have fundamentally aligned on to the consumer behaviour of wanting goods and services on demand and scarcity of time and attention span. Information and content is delivered and consumed on mobile phones, with GenZ and Millennial tech savvy consumers attending only to content that they find targeted, relevant and authentic. Customers of today, in addition to goods and service also want convenience, self-service and personalisation. Some common traits of the contemporary customer are, that they are well informed and self-educated, self-directed, fast paced, picky, contradictory, always connected, volatile and tech innate.

Beyond product and service innovation, new business models like freemium, pay-per-use, low monthly subscriptions are engaging consumers continuously to ensure sustainable revenue streams, reaching profitability and turning recent adopters into loyal customers. Thus, ensuring long lasting relationships with customers have become a key aspect for businesses. CRM has evolved gradually from Rolodexes of 1950s to Generative AI in 2020. What started as a record-keeping tool gradually evolved into digital documentation, sales automation, enterprise resource planning, and social marketing tools, to the present age hyper personalised automated communication form. The realm of CRM scope covers customer discovery, interactions, service, care, retention, and loyalty and is more often addressed as Digital CRM.

In 2022, the worldwide size of CRM software stood at USD 96.3 billion. The Total Addressable Market is set to grow to USD 290 billion. Salesforce Inc, an early mover and a global market leader grew 10x in revenue in a decade. In 2013, its revenue stood at USD 3.1 billion which stands at USD 34 billion in FY 2022. CRM, which started as a simple Rolodex, has evolved into a complex system laced with artificial intelligence that helps organisations manage customer data and engage them with it in a self-assisted automated format, bringing huge implications for cost, efficiency, and the experience of consumer communication.

Managing customer interactions with Gen AI and CRM

Gen AI has the potential to enable a better connection between brands and customers. This however requires creative ability to engage customers and ability to execute to deliver better performance results and employee experiences. A combination of Gen AI and CRM can impact functional domains of marketing, sales, commerce, service, and customer success.

Marketing

Gen AI capabilities are ideally suited for the marketing function which requires content creation and creative generation. It will enable marketers increase their output, efficiency, and creativity. It provides a cost and time effective option for producing text, images, creative briefs, multiple versions of ad campaigns with variations. Most crucially, it will help marketers create personalised and engaging experience for customers at scale. Additionally, it will enhance idea creation, productivity and data driven planning and execution for marketing teams. Content development and personalisation of creatives will come at a reduced turn around time and cost. Conventional content creation methods which are time consuming, lack hyper personalisation at scale across multiple content formats with data driven insights on consumer behaviour. Brands are thus able to communicate through the most relevant content and most effective media at speed. Gen AI can create content across diverse platforms from blogs to social media posts to email campaigns, with a nuanced data backed understanding of the target audience and at the same time ensuring that the designed format, tone, and campaign outcomes are in sync. These elements are the most crucial for scale.

Moreover, the ability to create versions of campaigns and content, marketers can execute A/B testing at speed and refine execution for optimal conversion. Ensuring standardisation of brand voice and tone with a synchronisation of specific target audience requirements with greater accuracy and speed, give Gen AI an edge over the conventional human creative teams. These are critical for brands with presence in multiple locations across different cultures and regional preferences.

Real time sentiment analysis, that not only establishes positive , negative or neutral sentiment across key words and topics associated with the brand, but also analysis activation across broad competitive set to inform competitive benchmarking and rating. These insights make marketing teams better equipped to execute data insight driven campaigns. Tools for gen AI production are largely simplified and don’t require complex integrations into existing workflows.

This, however, will require data management, tech stacks, governance, and operational capabilities for organisations to fully scale AI in marketing.

Sales

Product sales has evolved into providing tailored sales content across the customer’s early journey. Chatbots, real time Q&As, self-service portals, customised proposals and other features unlocked by Gen AI are not only reducing operational inefficiencies and administrative burdens but also enhancing the experience of purchasing products. Amongst key benefits of Gen -AI are :

• Automation of administrative and lower value tasks like data entry, meeting notes, proposals, sales script etc. • Implementation and management of streamlined sales processes at scale across products and locations delivering features sales service value at a lower cost.

• Training, onboarding and management of sales teams and resources can be done at speed and efficiency with increased standardisation in the sales pitches.

• Channel partner and distribution networks managed across multiple territories and products. Channel networks can get personalised content, lead management support, incentive plans, and gamified leaderboards. Across the sale value chain Gen AI increases seller speed and productivity and also reduces the experience friction.

Seller productivity gets efficiency by autoupdation of CRM using AI and machine leading to ensure that the sales pipeline data hygiene is maintained with a lesser administrative effort of data entries.

It ensures, that there are smart prompts that aid pre-sales and sales team to enable them take brand specific , user insight driven and sales goal oriented actions.

With Gen-Ais capabilities one case accurately gauge user interaction basis of past data and generate content tailored for the specific needs of the customers product or service requirements.

Sales enablement

Ensuring sales teams are equipped with the right set of product, service and consumer information with the right training content curated specifically to the sales member’s background. This is handy for large sales teams operating across multiple locations.

With voice to text features, automated note taking, calendar and meeting management, sellers’ capacity is offloaded of administrative and low value work thus maximising capacity utilisation.

Self-assisted customisation and configuration of products and services with real-time quotes and tailored pricing and offers ensure customer centricity in sales processes. The engagement becomes personalised, optimised and dynamic to the users requirements ensuring better experience of sale and probability of closure.

Buyer profiling, with preferences and pattern analysis help sellers understand their needs and provide a tailored outreach. Bais of customers sentiment analysis from its communication forms of call transcripts and emails a probability of conversion and lead prioritisation helps sales teams prioritise their sales pipelines.

Automated chatbots ensure human-like QnA experience with tailored yet standardised responses for customers ensuring they are kept engaged real-time and recommended products and services suited to their needs. Sales copilots also are an effective feature that help sales resources create specific communication to customer personas based on the stage of transaction.

Commerce / transaction

Every consumer engages digitally to consider or make a transaction. Gen AI features sets are reducing cart abandonment by delivering a hyper personalised buying experience with intuitive prompts by tailoring user journeys and promoting conversions. These tools ensure continuous engagement with the consumer for product information, comparison, pricing and delivery.

Tools that help customers across intuitive search, personalised recommendations, enhanced feedback loop and streamlined shopping experience.

Data driven personalises searches, recommendation and natural language bases search and recommendation options ensure quick transaction turnarounds. Product cataloguing and information listing becomes automated. Customers can also look at the products in 3 dimensions thus ensuring better visualisation and evaluation. With bespoke purchase plans, customer satisfaction and retention increase thus positively impacting sales numbers, experiences and band loyalty.

Customer service and customer success

Post transaction service experience becomes most critical for customers and brands alike considering the level of customised and tailored experiences that is brought on in the discovery and transaction phases of the user journeys. This is what leads to brand loyalty, repeatability of transactions and increased lifetime value of customers once onboarded on the brand or product portfolio.

Prompt, real time and accurate self-service capabilities ensure faster customer grievance management and resolution. Virtual and human agents engaged in customer service are laced with fit-for purpose scripts, prompts, information, and training with automated tasks like follow up emails, and calls. This brings a multi fold increase to agent productivity. Gen AI and LLMs can analyse a customer’s profile and with automated workflows cater to their potential issues.

With product catalogue assists there is an increase in cross sell and recommendations for customers increasing their wallet share efficiently. Agents are assisted with next best actions to ensure recommendations on additional products and features.

The true potential of Gen AI can be unlocked best when used in combination with predictive AI, voice to text, experience management and workflow optimisation.

In the customer success segment of the value chain, a faster time to value with efficient onboarding workflows ensure an improved customer experience and reduced customer churn. Training co-pilots, automated self assists bots and knowledge content driven prompts and actions ensure faster time to value realisation for customers.

Given the depth and breadth of AI capabilities that can impact customers across the user journeys from marketing, sales, transactions, service and customer success, organisations and teams need to ensure that they are upskilled with tech , workflows and capabilities to deliver an enhanced customer experience. This can be ensured by doing 4 critical things.

1. What are the customer services opportunities one can identify, prioritise and phase for execution.

2. On identifying the use cases which are most critical for business objectives, the next important thing is to choose the platform or solution to deliver Gen-A features to for the specific use cases. Are these solutions meeting user needs? Does the organisation have the ability to deliver these? and do these solutions generate business goals an revenues.

3. On onboarding the solution or platform, one needs to ensure capability building to adopt, use and monitor the feature set. The resources, organisational structure and operating model required to deliver the solution.

4. Fourth, most crucial aspect is idenfitying risks of adoption and implementation and impact on customer from a compliance and governance stand point.

Organisations that are constantly looking to improve customer interactions, create hyper personalised and differential experiences for their customers, and improve their operational efficiency will be the fastest to catch on to the Gen-AI driven revolution in customer relationship management space. Customers are ready , can organisations upskill, upgrade and uplift their game ?

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