Strive Group Sees 20% Increase
in Weekly Sales Within 21 Days

Company Overview

Strive Group is a connected experience agency that turns touchpoints into talking points for businesses that care about their brand, employees and customers. From delivering Interactive Customer Experience (ICE) solutions to launching comprehensive brand strategy and planning projects, employee learning and development events, and more, Strive Group creates exceptional experiences for businesses, their employees and customers.

“Aible gives us a real unique selling proposition and could be a massive revenue generator. We inserted the Aible lead scoring into our CRM system and within two days there were rumors going around our company that accounts with higher Aible scoring were getting higher bookings. Within a week, Aible recommendations produced a 20% improvement over the previous week in positive outcomes.”

– Alistair Grant, Co-Founder and CEO, Strive Group

two sided icon
Industry

Customer and brand services

Founded

2001

Based In

UK

Website

www.strive-group.com

Tech Stack

Five CRM, Excel, Aible

Challenge

In one of its divisions, Strive Group fields a team of customer experience experts who call Audi, Volvo, Jaguar, Land Rover, and Honda customers to book automotive services and increase brand dealership revenue. Strive aims to optimize its customer contact operations for one large client by identifying customers more likely to make a booking to have their car serviced or MOT-certified at the dealership. The goal is to get more bookings while lowering the call rate from 125 calls per day to 100 calls to free up customer contact operatives. Strive turned to Aible to help predict which car owners were more likely to make a booking at a dealership so they can more efficiently use the systems they have in place and improve them. Strive wanted to obtain a weekly scored list of customers, and also to gain new insights into the drivers that make customers more or less likely to have their car serviced.

Project Stakeholders

Led directly by the CEO and Co-Founder, the project was supported by two additional members from the data and analytics team.

Aible Solution

Within two weeks, Aible delivered a scored list of customers and these predictions were made available in their CRM system. In just three days after production, end-users realized the value of AI predictions. Finally, within a week from production, Aible helped Strive record a 20% improvement in positive outcomes and identify £130,000 in annual savings. Similar potential gains were identified for 60 additional customers. Aible uncovered key drivers of customer behavior so that Strive Group can better understand how certain characteristics make customers more or less likely to have their car serviced at the dealership. As a result of the successful AI project, Strive is transforming its business model to lead with Aible, so that it can position itself as data analytics experts to new and existing customers.

Quick Win Tips

Aible Solution Timeline

Day 1

Data Enrichment, Custom Blueprint, Model Training

current image

Day 7

Recommendations to End Users

current image

Day 21

20% Increase in Weekly Sales

current image

Day 1

Data Enrichment, Custom Blueprint, Model Training

current image

Strive worked with Aible to clearly define the use case, understand the business goals and customer contact center capacity constraints, set timelines, and identify what data Strive Group would provide to train AI models. The AI would be trained on 60,000 Strive service call records collected over a 3-month period.

Day 7

Recommendations to End Users

current image

Aible enriched Strive’s data to gain additional insights and add value. By leveraging postal code information showing the relative locations of customers and a targeted dealership, Aible found that owners of specific vehicle brands and models were more sensitive to distance from the dealership than others when it came to booking a service call. Further features were added to represent absolute date fields as relative periods - for instance, the actual date a vehicle was registered has little impact on the models, whereas the age of the vehicle is a significant factor. Likewise, the date of the previous service is largely irrelevant but the time elapsed since the previous service is not. A custom blueprint was developed based on business assumptions and cost-benefit tradeoffs unique to Strive. This blueprint can be used by Strive for future model training and as a foundation for additional AI projects. More than 400 predictive models were trained and sequenced enabling dynamic and rapid scenario planning at the subgroup level. Over 20 unique model driver variables were identified, such as whether service is overdue, how many days until servicing is due, days since last service, days since last visit, and vehicle age. These drivers were ordered by significance at the field and value level to determine which attributes are more likely to result in a successful booking. Multiple model drivers were identified across different dealership types that have a significant impact on whether a customer will make a booking.

Day 21

20% Increase in Weekly Sales

current image

Strive put Aible predictions to the test. They gave the scored customer list to their customer contact team and had them use the predictions to guide their calling strategy. In just one week with Aible predictions, Strive saw a gain of 2.5% in positive bookings, yielding estimated annual savings of £200,000.Larger potential gains were identified for possible future calling strategies. For instance, Aible found that 29% of Strive’s calls were being made to just 12% of the customers, and recommended a different mix based on dealer segmentation. The test demonstrated that a negative prediction from Aible was a good indicator of customers that would need repeated calls and yet still not make a booking. Using the predictions to selectively reduce the number of calls could result in saving about 1,275 calls per week and freeing up agents for other duties.

New Areas Of Growth For Strive Group

Strive Group is already using the successful Aible Immediate Impact project as a launch pad to win new business and position themselves as an AI-powered solution. In addition to customer contact center optimization, future use cases also include fleet sales optimization.

“From the work we’ve done so far with Aible, we’re now restructuring our business, so we make it part of what we do. We’ve changed teams around, and we’re looking for an analyst that can live and breathe this every day. We’ve changed the contact team so that there’s more of a team leadership role – the data team can just be responsible for the data. We’re also looking at changing our CRM system, so that we lead with Aible. Aible scoring will show us when and how often to call.”

– Alistair Grant, co-founder and CEO, Strive Group

High Value Use Cases

Industry_Telcom-2
Retail-Aug-27-2021-08-50-01-56-PM
Industry_Higher_Ed-2
Industry_Healthcare-1
Industry_Banking-1
Industry_Insurance-2
Industry_Government-1

High Value Use Cases for Telecommunications

The telco industry continues to experience rapid change as consumer behavior shifts towards telecommuting, and the 5G rollout promises to open new opportunities. Aible helps telco companies reduce customer churn by targeting customers with the right tactics to maximize lifetime value at the lowest possible cost, while also optimizing leads across different product lines and sales groups. Aible also helps call centers increase customer satisfaction by proactively routing calls to the best available service group based on lifetime value and the complexity of the service call.

High Value Use Cases for Retail

The retail industry continues to be under tremendous pressure from online competitors and a more demanding consumer base. Aible helps leading retail organizations optimize and personalize promotions to maximize cross-sell and up-sell opportunities, monitor and take action against inventory loss from fraud and employee error, decide when to expedite inventory to match demand spikes, and reduce avoidable returns. Aible also helps retail stores optimize inventory, logistics and staffing, and make better data-driven decisions that take into account the long-term value of customers and how to prioritize them.

High Value Use Cases for Higher Education

Artificial intelligence is rapidly being adopted by Higher Education to improve student and faculty outcomes and optimize institutional initiatives. Aible helps higher education institutions anticipate enrollment trends, optimize recruitment efforts, elevate academic performance, improve alumni donor outreach prioritization and more. With Aible, institutions can create segmented retention strategies for different sets of students and target them with highly personalized messages to retain them.

High Value Use Cases for Healthcare

The healthcare industry faces increased pressure to leverage technology to deliver better patient outcomes at lower costs. Aible helps leading healthcare organizations increase the quality of care, improve operational efficiency, and reduce fraud, resulting in increased revenue, reduced cost, mitigated risk, and better health outcomes. Aible enables providers to predict in advance patients likely to miss appointments and proactively contact them to improve healthcare and reduce clinician downtime as well as determine which members are likely to churn in order to target them with the optimal tactics.

High Value Use Cases for Banking

Banking leaders are already applying AI to win new business, evaluate creditworthiness, and reduce fraud, resulting in increased revenue, reduced cost, and mitigated risk. Aible helps banks reduce customer churn by gauging the risk of losing high-value customers and optimize sales by predicting the likelihood of a customer purchasing a given product, while optimizing the sales team’s resources. Aible also mitigates credit risk by identifying high-risk applicants to avoid unnecessary debt collection.

High Value Use Cases for Insurance

Leading insurance companies are already applying AI to predict how customer needs are evolving, improve claim management, and reduce fraud, resulting in increased revenue, reduced cost, and mitigated risk. Aible helps insurers optimize leads across different product lines and sales groups to maximize profits and determine which policies are likely to churn in order to increase retention. Aible also improves fraud detection by predicting which claims are likely to be fraudulent to optimize claim investigation resources and quickly process valid claims.

High Value Use Cases for Government

Governmental agencies are increasingly being asked to do more with less. The recovery from COVID places new demands, even as budgets tighten. Aible helps governmental agencies improve employee recruitment by identifying top candidates to pursue based on past outcomes and optimize employee retention by identifying employees at the greatest risk of churning in order to take early action. Aible also improves child and domestic welfare by identifying cases that are likely to require early intervention and mitigates unemployment fraud by proactively flagging fraudulent claim submissions.

Resources

eBOOK

5 Quick Wins to Accelerate Value from Your CRM

Customer Relationship Management (CRM) platforms are good at telling a sales team where they are and how they got there.

ON DEMAND WEBINAR

Strategy-First: 
The Key to AI Success

Businesses often unwittingly deploy a set of tactics with their AI that’s in conflict with their overall strategic objectives.

BLOG

Make CRM Smarter with AI

CRM software has created plenty of operational efficiencies, helping sales teams navigate customers through the entire lifecycle, from sales lead to company advocate. At its best, CRM helps sales teams