Synopsis
When the international sustainability team at Google challenged Fastloop’s model against a number of other benchmarks in the market. The Fastloop model beat everything they could find, combine, or build. In this proof-of-concept (POC), Fastloop delivered a data-driven mobile application that predicts lead scores and seamlessly integrates into the sales workflow.
Highlights
Custom-built application revealing cost savings and progress toward net-zero goals
2500+ rows of customer data for the POC phase
90% of captured records were proven accurate exact matches
Challenges
Black & McDonald had identified a substantial growth opportunity in offering sustainability initiatives to new and existing customers by using data to identify net new opportunities. This came with key challenges.
Core challenges include:
There was a resourcing shortage in scoring and prioritizing customers based on their sustainability potential required analyzing disparate datasets (e.g., Salesforce, emissions, and address data).
Field staff and sales teams need digestible and actionable recommendations, which requires responsible handling of data sources.
On-site field-technicians are often in locations where internet connectivity may be weak or non-existent, demanding solutions with offline access and seamless reconnection.
Solution
Fastloop developed a proof-of-concept application using Google AppSheet and BigQuery that presented a calculated lead score and other emission factors. It is a data-driven solution that enables the Black & McDonald sales team to reach the right customers and provide them with insight into the products and services offered by Black & McDonald.
Key components of the solution:
- Multiple data sources are modelled and ingested into an optimized database, including Black & McDonald’s backend ERP system with customer information, Salesforce data, emissions data (third party), address data (third party), and more.
- A formal data pipeline into BigQuery ensures that there is ongoing data integration that keeps recommendations and suggestions up-to-date.
- Custom-built machine learning models analyze the data to score organizations on their sustainability efforts. The scoring model itself was created by Black & McDonald, with Fastloop pulling in the right data and properly weighting it to generate the precise scores that Black & McDonald sought.
- Employees access a mobile application built with Appsheet that uses these scores to recommend new and existing customers to target with specific products and services. This not only arms employees with leads, but also provides them with the reasoning and data to back up the sales pitch.
Integration of the right third-party datasets
Fastloop worked with Black & McDonald to find datasets that could be leveraged to determine different factors in sustainability. These datasets are not particularly valuable on their own, but by leveraging data expertise and introducing AI solutions, Fastloop quantified the real impact organizations were having on the environment.
A low-code app with simple maintenance
The mobile app that salespeople and service techs use to understand and present information to their customers was built in an easy and configurable way using no-code solutions; Black & McDonald can manage it themselves without additional costs or ongoing management by Fastoop.
Results and Impact
This proprietary tool helps customers understand their bottom-line cost savings, how they align to macro environmental policies, and how they can continually shift towards a net-zero carbon emissions future.
The calculated lead score and other emission factors contributed towards driving Black & McDonald’s incremental top line revenue.
Why Fastloop.ai?
Fastloop stood out amongst other technology implementation partners during a competitive process. Black & McDonald valued how Fastloop would approach the solution after careful review.
Industry knowledge and a strong business perspective
The preparation and research that Fastloop did to supplement their existing knowledge about the construction industry helped display how data-driven analytics and solutions could truly advance the organization from a business perspective.
A complex solution, deployed quickly
Black & McDonald’s desired solution was complex, touched many teams, and needed to be operational quickly. Fastloop was strategic and tenacious in laying the technical foundation, as well as providing a robust training plan for non-technical employees to take advantage of the solution.
Willingness to invest
While other potential partners were inflexible in their terms, Fastloop co-invested in the project to both meet client budget and demonstrate their passion for the solution built.
Future Outlook
A key facet of proof-of-concept delivery for Black & McDonald is the roadmap that provides a path to broader operationalization. Future capabilities include:
Automated Ingestion of New Data
Moving away from manual data loads can expedite operations and help scale the solution.
Explore New Data Sources to Further Improve Scoring Capabilities
By analyzing new datasets and exploring the use of machine learning models to integrate into lead scores, the reliability and effectiveness can be improved.
Additional Product and Service Recommendations
Insights from the lead score could be provided to sales reps and field techs at the point of sale or service.
AI Agent to Assist Sales with Additional Recommendations and Predictions
An embedded sales assistant in the application can provide Black & McDonald employees the ability to ask specific queries about companies to target and the largest assessed opportunities.