Acquiring new customers is getting increasingly challenging for businesses in 2024. Between eroding brand trust, walled gardens limiting marketing reach, and rising ad costs across channels, traditional acquisition strategies are losing traction. On the flip side, leveraging customer service and customer experience as revenue growth engines remains largely underutilized by a majority of companies.
This represents a massive missed opportunity. With the right applications of data, artificial intelligence (AI), and automation, customer retention and expansion can drive superior return on investment (ROI) compared to acquisition. It creates sustainable growth fueled by happy customers transforming into influential brand advocates.
By taking an AI-first approach to customer service, companies can lean into their strongest antidote to acquisition challenges—their current customer base.
For small and mid-sized businesses especially, acquiring customers through traditional channels like search, social, and paid advertising has become exceedingly difficult:
Google now displays featured snippets and video carousels above the core search results. Their stated goal is to provide quick answers so searchers don’t have to click elsewhere. This leaves fewer visitors making it to actual websites. For those that do, getting onto the first page itself requires meticulous Search Engine Optimization (SEO) and page speed optimization efforts.
Paid advertising costs on platforms like Facebook, Instagram, YouTube, and Google continue to climb. On Facebook and Instagram specifically, changes to Apple’s IDFA policies have led ad prices to spike over 40%.
The proliferation of misinformation, multiplicity of brand messaging everywhere, and concerns over data privacy have dissolved much of the trust customers previously placed in businesses. Reviews from friends and third-party sites like Yelp and G2Crowd now hold more weight compared to company claims, see BrightLocal consumer survey.
This diluted brand loyalty is reflected in consumer behavior as well. A majority expect businesses to respond within 30 minutes on social media (see SproutSocial data) and prefer asynchronous conversations over calls. Impatience is rising and so are demands for hyper-personalization.
Without fundamental asymmetrical value addition, it becomes challenging for brands to rebuild once eroded - as new competitors are always a click away.
On average, the likelihood of selling to an existing customer is 60–70%. Compare that to the 5-20% chance of converting a new prospect validated by HubSpot customer surveys.
Also, retaining customers can cost ~25x less than acquiring new ones, as calculated from an in-depth Totango marketplace analysis.
Platforms like Facebook and Instagram actively dissuade users from leaving their walled gardens. The algorithm skews heavily towards recommending native content from friends and family rather than branded posts.
To be relevant, businesses now have to tailor separate content strategies - one for their owned sites and one specifically engineered for each social media channel. This splits budgets and resources. Despite producing more high-quality content than ever before, the return on marketing investment (ROMI) is diminishing.
In summation, rumors of the death of traditional acquisition strategies are not exaggerated. For long-term viability, companies need to evolve - reducing dependence on volatile external platforms and doubling down on what they already own: their customers.
While current customer acquisition is proving difficult, for most businesses over 75% of revenue gets generated through repeat purchases and upsells to existing customers.
On average, the likelihood of selling to an existing customer is 60–70%. Compare that to the 5-20% chance of converting a new prospect (validated by HubSpot customer surveys). Also, retaining customers can cost ~25x less than acquiring new ones, as calculated from an in-depth Totango marketplace analysis.
No external entity understands a company’s products and customers better than its employees. These insights translate into an unparalleled capacity to create helpful educational resources, resolve concerns accurately, and recommend perfectly fitted products - as showcased by Petco's 6X jump in NPS through AI-guided customer journeys.
84% of customers are willing to refer brands that deliver excellent service. Effective promoters amplify branded messaging to new audiences at no added acquisition costs while providing invaluable social proof of concept. They willingly contribute user-generated content and recommendations showcasing personalized success with the product. In a world where new visitors entrust the advice of customers over marketers, this organic evangelism accelerates trust and conversion faster than traditional advertising.
To actualize this potential, businesses need to overhaul their customer service capabilities - evolving from reactive issue resolution to proactive lifetime relationship building. The next section summarizes an AI-powered framework to accomplish this.
The AI-CX Framework - Engage, Guide, Grow
Here is a three-stage framework to harness conversational AI, machine learning, and analytics for revolutionizing the customer experience:
I. Engage
a. 24/7 Availability via Conversational Interfaces
Conversational AI, including chatbots and voice assistants, now possess the ability to accurately resolve queries around the clock. When faced with complex issues, these AI-powered assistants seamlessly transfer conversations to live agents. This technology has become a game-changer for many brands, such as Sephora, who have leveraged personalized beauty advice chatbots to significantly boost their conversion rates.
b. Omnichannel Customer Service Orchestration
AI-enabled routing engines streamline requests from all channels into a single dashboard. The rules engine can assign inquiries based on wait times, customer history, issue urgency, and agent skills.
c. Swift Identification of Usability Pain Points
Analyze aggregated conversation data to rapidly uncover usability issues. Connect feedback to corresponding functions and engineering teams.
II. Guide
a. Proactive Churn Prediction using Machine Learning
Leverage gradient boosting algorithms to classify users based on behavior indicative of the risk of churn. Target them with re-engagement campaigns - validated by TD Bank's 20% call volume reduction through such AI-orchestrated customer guidance
b. Personalization Engine for Upsell Recommendations
Build rich visitor profiles incorporating demographics, past purchases, and content engagement. Match resultant segments with best-fit products and services for personalized upsell.
c. Curate Educational Touchpoints
Analyze the customer journey to identify milestones, common pitfalls, and inflection points. Deliver relevant tutorials, how-tos, and industry perspectives right before these occurrences.
III. Grow
a. Automated workflows for customer re-engagement
Schedule check-ins post-purchase with relevant educational collateral. Seek product feedback, suggestions, and testimonials. Measure satisfaction through NPS surveys.
b. Incentivize referrals through gamification
Encourage referrals by introducing loyalty programs, points-based rewards, and community engagement avenues like forums. Leverage principles of gamification and variable rewards.
c. Continual content enrichment
Recommend related reading to website visitors based on browsing patterns. Showcase exemplary customer success through case studies and community spotlights.
Essentially this revolves around tapping AI to know your customers better - and leveraging automation in conjunction with the human touch to nurture relationships with them. Now we turn our attention to critical organizational activations to actualize this at scale.
Organizational Activations - Teams, Metrics, Processes
1. Cross-functional Squads
To build a comprehensive view of the customer, specialized teams need to tear down silos. Marketing, Sales, Cloud engineering, Dev teams - all have separate insights on website visitors/customers. Enable visibility through unified data lakes. Provide self-service access to decision-makers across squads. Set up scheduled data syncs and shared scoring models for alignment.
2. Key Metrics Tracking
Evolve from narrowly tracking sales qualified leads and net promoter scores. Build full visibility into the complete buyer journey with touchpoint tracking and lookalike modeling. This allows the creation of micro-conversion funnels underpinning each interaction. Prioritize customer lifetime value (LTV) over acquisition.
3. Interlinked Workflows
Interlink workflows across service, sales, and marketing systems. Shared customer intelligence allows teams to trigger targeted campaigns, expansion offerings, and renewals at scale. Automate data capture from AI- Customer Service interface into the CRM post-call resolution.
The Way Forward
Consumer trust in brands is declining and costs of customer acquisition are prohibitive. Just chasing new customers fails to build sustainable models. However, businesses already own their best asset - their current customer base. AI and automation can help uncover their needs, guide them, and nurture enduring relationships.
Companies that transform customer service into trusted partnerships will be best positioned to come out ahead in 2024 and beyond. The choice is clear - embrace these emerging technologies to grow, or risk getting disrupted instead.