Accelerate Customer Acquisition with AI-Powered Personalization
A 2020 Forrester report commissioned by IBM stated: Firms’ personalization strategies do not translate to customer reality. 90% of firms say personalization is imperative to their overall business strategies, but they are missing the mark when it comes to relating to consumers. More than half of consumers say they feel brands are trying to get to know them, but they don’t see their shopping experiences improving because of it. Firms see budding success with flawed personalization strategies, but potential is endless if it’s done right. Even with immature personalization strategies, firms see benefits. From a commerce perspective, they lead to an almost 6% increase in sales revenue and 33% increase in customer loyalty and engagement. For marketing, it’s an 11% decrease in marketing costs. 1
According to Gartner by 2025, organizations offering a unified commerce experience by frictionlessly moving customers through journeys will see at least a 20% uplift in total revenue. The revenue uplift will come from three factors: conversion/acquisition, average order value, and customer retention/repeat purchases. 2
AI-powered Personalization in Customer Acquisition Accelerates Key Sales & Marketing Metrics
Organizations are leveraging AI-powered personalization to drive numerous sales and marketing key performance indicators (KPIs):
- Conversion Rates:Conversion rates are not only important for prospects converting to customers, but there is interest in improving conversion rates at every stage of the sales cycle, e.g. from anonymous lead to qualified lead to prospect.
- How can personalized insights or personalized shopping experiences improve conversion rates (or reduce churn)?
- How do we personalize shopping experiences and offer or product presentations in order to improve conversion at each stage of the sales funnel?
- Intelligent Lead Generation
- How do we improve the quantity of leads with more personalized (and possibly cheaper) ads?
- How do we improve the quality of leads by knowing more about individual leads upon arrival at our website?
- Can we optimize ads and lead generation campaigns to drive more targeted communications at lower costs by understanding leads, prospects and customers better?
- Cross-sell and Up-sell Rates - and Retention
- How do we understand customers at a much more granular level of detail, a more personalized level, in order to present them with product upgrades and extensions that drive revenue and retention rates?
AI-powered personalization solutions need to deliver hyper-personalized insights to customers and consumers in order to improve these KPIs.
AI-powered Personalization in Customer Acquisition Goal: Improve Key Metrics Across the Sales Cycle
AI-Powered Personalization in Customer Acquisition: Use Cases
AI-powered Personalization use cases and the hyper-personalized insights that they produce include:
- Intelligent Lead Generation: Improve the quantity and quality of leads through personalized insights about website visitors and other prospects. Improve the effectiveness of ad spend with more targeted ads that might also be lower cost.
- Personalized Shopping Experiences and Offer Presentment: At each stage of the sales funnel, understand personal preferences earlier in the shopping process so that leads and prospects can have a more personalized shopping experience, including more personalized offer or product presentment.
- Cross-sell & Up-sell Insights: Provide personalized insights into customers that can drive improved cross-sell and up-sell conversion rates - and enable more teams across the enterprise to use these insights, e.g. beyond sales, empower customer service and self–service channels to use these insights.
- Churn & Conversion Analysis: Understand why leads and prospects convert to the next stage or churn out of contention.
- AdWord Optimization or Ad Success/ Failure: Understand leads and clients better in order to deliver more personalized and granular personas to market to.
- Personalized Communication Preferences: The right message at the right time via the right channel requires hyper-personalized insights into consumers.
- Product Intelligence: Based on learnings or feedback from shoppers, translate conversion and churn insights into product development insights, e.g. pricing and product features that lead to better conversion rates.
According to Capgemini, contextualized personalization at scale aims to generate immediate sales transactions as well as brand loyalty by engaging with consumers in real-time. Marketers should establish their customer profiles to best decide the approach to ‘moment marketing’ across various channels and touchpoints. Outcome: Experience suggests that 90% of identified leads will be valid, the lead conversion will be up to 10% points higher, the retention of potential churn customers 20% higher, and the accuracy for up-selling recommendations will be 400% higher. 3
Challenges with Personalization in Customer Acquisition
Organizations looking to leverage AI-powered personalization solutions in Customer Acquisition are challenged in a number of ways:
- Creating a personalized first impression with customers as soon as possible. Relevant, engaging messages will encourage clients to purchase from you.
- The rising cost of customer acquisition. Cost per acquisition (CPA) has been rising steadily.
- The complexity of today’s buyer. Today’s buyers are more self-directed and they’re likely to base much of their decision-making on information they find online. When buyers do interact with sales reps, they expect a continuous and personalized experience.
- Customers churn quickly.
- Challenges with AI-powered Applications that Leverage Personalization
- Data collection in support of personalized insights
- Turning customer data into personalized insights
- Personalized insights that deliver hyper-personalized shopping experiences and product presentment
- Productionalizing and operationalizing personalized sales insights as AI-powered applications
According to Gartner, 63% of marketers face a moderate or significant challenge in delivering personalized experiences to customers. 4
Solution: CognitiveScale’s Cortex Enterprise AI Platform & Profile-of-One Technology
The key to valuable AI-powered Personalization in Customer Acquisition is to create a rich profile of Leads, Prospects and Customers powered by AI that includes personalized insights. These insights then drive actions across all systems of engagement or sales channels.
CognitiveScale’s Cortex Enterprise AI platform accelerates the AI application development life cycle for personalization use cases in Customer Acquisition:
- Connect and curate data and models that leverage existing data and data science investments (e.g. conversion and churn models)
- Orchestrate the components and compose AI applications from models, algorithms and rules engines (or a combination of multiple of these)
- Drive personalized insights via proprietary skills and capabilities like our Profile-of-One capability
- Learn via feedback loops that improve model and application performance
- Govern AI applications to ensure trusted, responsible use of AI
Cortex’s Profile-of-One technology is a core capability that:
- Provides a 360° view of an entity - from anonymous leads to prospects to customers
- Includes declared and observed data as well as inferences about an entity
- Provides personalized insights through learning and interactions
- Stores important attributes about an entity to effectively deliver the right insights at the right time (context) and at the right place (channels)
- Enables key business outcomes & KPIs using metrics
Our AI-powered Personalization White Paper includes a deeper dive into CognitiveScale’s Cortex Enterprise AI Platform and Profile-of-One Capabilities.
Contact us to explore how we can help your organization to transform Customer Acquisition with AI-powered Personalization.