How Did LTM Help One of the Largest Automobile Enterprises in the US Unlock Smarter Lead Nurturing with Salesforce’s Einstein AI Predictions

Why AI Is Crucial for Marketers?

Digital innovations in the customer experience and engagement space are driving massive shifts in customer preferences and purchasing patterns in the new normal. It is more important than ever to identify and engage the right audience with the right messaging. Towards this end, marketing thrives on segmentation, targeting, and positioning, and every business, irrespective of size, geo-spread, and offerings, must strive to get them right.

For instance, smart personalization alone can deliver more than 5X marketing ROI and increase sales revenue by more than 10%. However, most enterprises struggle to make sense of big data collected from various devices, channels, and touchpoints. Traditional data analytics alone fails to provide actionable insights and identify trends. This is where harnessing AI and predictive models are the keys to unlocking the power of these huge volumes of customer data. 

Customers who have strategically invested in Salesforce technologies can harness Einstein Analytics and Discovery, an ethically designed AI engine for the Salesforce ecosystem. It is the first comprehensive AI for CRM and is available through Sales Cloud, Service Cloud, Marketing Cloud, App Cloud, Analytics Cloud, and Community Cloud.

Customer overview: - Einstein to the rescue. How LTM helped a customer in the automobile sector.

LTM recently helped one of the largest motorcycle companies in the US to embark on a journey to create personalized customer experiences powered by integrated data and insights collected across digital touchpoints. LTM helped customers transition to a centralized Marketing Orchestration platform providing agility and scalability toward creating exceptional customer experiences.

An AI solution helped activate customer segments across channels and enabled smart lead nurturing. The goal was to engage customers with relevant, timely communications and drive conversions to their eCommerce platform. The solution leveraged smart profiling, engagement tracking, and multi-point validation of customer interests across platforms.

Challenges

The customer needed to improve their CX through a mix of tactics and strategies. 

• They needed help to reduce customer cannibalization and revenue shrinkage due to targeting via competing campaign initiatives.
• They also required the ability to identify customers’ intent/interest and measure their engagements across website, eCommerce purchase, email, and mobile app.
• They also needed to orchestrate customer engagement in specific products/categories through meaningful intent/interest detection and AI predictions

Solution levers

• Leveraged custom ML algorithms(XGBoost) for scoring subscribers.
• Scoring based on customer behavioral & demographic data.
• Built multiple scoring models based on various campaigns.
• Leveraged out of the box salesforce features to configure flow for scalability.
• Scoring leveraging Sales Cloud & Marketing Cloud.
• Marketing journeys powered with AI Model predicted scores.
• Data driven approach to maximize reach and conversion.

LTM Solution

• Analysis: our team performed a deep analysis of 180 + customer data points across several platforms, including web analytics, SF-CRM, eCommerce platform, and SF-Marketing cloud. We shortlisted 60 critical attributes that had a higher correlation to intent/interest display and prioritized them for building the AI predictive model. 
• AI model and simulation: leveraging the Salesforce Einstein Discovery platform, we engineered a predictive model that could calculate product-wise engagement scores. Multiple models were simulated using selected data points to determine the best AUC (area under the ROC curve).
• Prediction score: the prediction score derived was a numerical representation of a consumer’s likelihood to purchase a product based on a series of past engagements displayed across a range of platforms. The prediction scores were grouped into range buckets to be used for segmentation and customer cohort creation.
• Orchestration: marketers gained the flexibility to easily target consumers based on the recency or frequency of a specific type of product interaction. Further, we leveraged Einstein for marketing to optimize and craft email sends

Salesforce tech-stack: Einstein Discovery, Marketing Cloud, CRM Analytics, and Sales Cloud. 

Key benefits

• A unified data model aggregating customer attributes from varied sources.
• A time-decaying lead scoring model with dynamic weightage.
• Improved customer segmentation honoring the customer intent/interest across platforms and channels.
• Increased eCommerce purchase conversion metrics.
• Prioritized customer outreach and engagement metrics. 
• Faster time-to-market with go-live in 6-7 weeks.
• Reduced cost on tooling & feature enablement.
• Quicker campaign launch timelines.
• Improved email re-engagement rate.

In a Nutshell

This Salesforce-native solution by LTM can be easily customized to help organizations move towards engaging with their customers based on intent/interest signals processed from several channels and platforms. The prediction scoring is much more mature than traditional linear lead scoring solutions that ignore key considerations like recency and time decay.

INDUSTRIES

• Retail
• Banking
• Financial Services
• Insurance
• Travel and Hospitality
• Automotive
• Consumer goods

To learn more about how LTM’s Salesforce marketing oering can help your business get to the future, faster, please reach out to our Salesforce Marketing experts at info@LTM.com.