Data Transformation to Enable Advanced Analytics and AI
Our client needed a modern, transformative data architecture to reach the next level of analytics, including AI.
The transfer of marketing leads to sales teams is critical for customer acquisition, however our client’s process was time consuming and heavily manual. RevGen built a proof-of-concept solution that automated the entire handoff.
Our client, a leading national telecommunications provider, thrives on robust marketing strategies that demand precision and efficiency. They manage a vast network of contacts and leads, leveraging sophisticated scoring and prioritization systems across a complex software stack to power their account based marketing initiatives. By harnessing the power of Logic Apps, Synapse, and other Azure tools, we streamlined their processes to deliver highly qualified contact records in the exact format they need, right when they need it.
Our client needed a solution for their contact record data that could handle their diverse technologies as well as improve efficiency while navigating their siloed structures and complex end-user requests.
Our client uses a diverse Martech stack with silos around lines of business and the steps of the marketing process. Their current technology solutions include Salesforce, Marketo, Oracle, and custom scoring processes in Azure.
Requests for data were incredibly varied and poorly formatted, leading to manual processes. Incoming data were in spreadsheets, with search instructions that spanned a variety formats and positions.
Because these processes were intensely custom and human-dependent, and because request volume was inconsistent with huge volumes one day and no requests at all another day, delivery time was slow, often measured in days or even weeks.
Desired outputs for the records were diverse, too. Internal customers were looking for spreadsheets, email bodies, or contact records set up as campaigns in Salesforce. Because the existing processes were executed by human operators, internal customers were used to asking for whatever they wanted – including custom field sets and different delivery formats.
We developed a service-oriented solution, inspired by a layered API architecture, to streamline and modularize input, logic, and output. This approach not only enhances efficiency but also promotes reusability across multiple processes and request methodologies, delivering a flexible and scalable solution.
During our short and targeted engagement, RevGen developed a proof-of-concept that showed our client a path to automating complex business processes and opened the door to forward–looking solutions that deliver business value.
We developed the ability to ingest incoming requests where they exist, processing the spreadsheets already in use within the business, while also creating the backend components that allow those requests to be API calls in the future. Our new process supports multiple points of entry in ways that work for the users. We also set parameters to handle custom aspects of a request, so users did not have to fall completely into a specific box, maintaining the flexibility they enjoyed.
Using Logic Apps, Functions, and other Azure components, we were able to build powerful logic processes that navigated the breadth of our client’s technology infrastructure. Interacting with external systems like Marketo and Oracle, able to execute API calls to vendors to enrich data, leveraging internal data assets like scoring and prioritization models.
Our process supports diverse requests and desired formats, from returning a spreadsheet to a user’s email, to building a campaign of new contact records in Salesforce. And it can integrate next steps our client hasn’t even imagined yet – like a chatbot that responds to requests with leads and lead information in real time.
Our proof-of-concept showed significant benefits, improving efficiency from both a time spent and manhours perspective, while maintaining the kind of user experience our client required.
Returning leads through our automated process reduces per run manual labor costs from several hours per request to zero.
In sales processes where days can mean double-digit difference in close rates, we reduced processing time from days to minutes. In previous iterations, our client relied on multiple people in multiple departments executing their steps in order, one at a time. The current process runs end-to-end in one automated flow.
Getting data faster and lowering the costs of getting data empowers salespeople and their leadership to think creatively and to be aggressive in their campaign planning.
All of this rolls up to the two bottom line metrics: more sales and more revenue.
Our client needed a modern, transformative data architecture to reach the next level of analytics, including AI.
Improving data quality was key to ensuring our financial services client retained data integrity and accuracy while also reducing time and money spent on after-hours issues.
To improve sales efficiency, our client needed an “At-a-Glance” customer segmentation model that could evolve with their business.
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