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Databricks > Case Studies > Boosting Customer Conversion with Conversational AI: A Case Study on Aktify
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Boosting Customer Conversion with Conversational AI: A Case Study on Aktify

Technology Category
  • Platform as a Service (PaaS) - Application Development Platforms
  • Robots - Parallel Robots
Applicable Industries
  • Cement
  • Utilities
Applicable Functions
  • Sales & Marketing
Use Cases
  • Time Sensitive Networking
Services
  • Data Science Services
The Challenge
Aktify, a company specializing in conversational AI, aims to help its clients convert their customers through AI-driven SMS conversations. The company's goal is to make these AI agents as effective as possible, which requires drilling into massive volumes of data to find overlooked insights. However, Aktify faced challenges in managing its complex data dependencies, which hindered data democratization. The company needed a way to allow different teams to interact with data as per their needs. For instance, while a data scientist might need raw data, an executive team would prefer pre-aggregated data for quick decision-making. The company also sought to minimize the risk associated with data transformations and to make data management more simple, flexible, and cost-effective.
About The Customer
Aktify is a technology company that specializes in conversational AI. The company's primary goal is to help its clients convert their customers through AI-driven SMS conversations. Aktify's clients can use a conversational AI agent to conduct thousands of SMS conversations with sales prospects simultaneously. With Aktify’s solutions, the average customer generates $227,000 in revenue per year and achieves a 19x ROI. Aktify works behind the scenes to make these AI agents as effective as possible, which involves drilling into massive volumes of data to find overlooked insights.
The Solution
To overcome these challenges, Aktify implemented the Databricks Lakehouse Platform and dbt. The Databricks Lakehouse made data management simpler, more flexible, and cost-effective, while dbt made data transformations easier and more reliable. This combination allowed employees with minimal SQL skills to work directly with data, democratizing data throughout the organization. The Delta Lake on Databricks ensured reliable performance and streamlined troubleshooting, enabling Aktify to roll out new functionality releases more quickly. Additionally, Aktify used Databricks Utilities to find answers in less than a day, significantly reducing the time previously required for its data science team to build complex scripts to query databases. The company also used a one-click Tableau connector in Partner Connect, allowing all users to create their own Tableau dashboards.
Operational Impact
  • The implementation of Databricks Lakehouse Platform and dbt has significantly improved Aktify's operational efficiency. The company has been able to democratize data throughout its organization, allowing stakeholders to make better-informed decisions. The solution has also reduced the risk associated with data transformations, making data in production accessible to anyone on Aktify’s staff. The time travel functionality of Delta Lake on Databricks has streamlined troubleshooting, enabling Aktify to roll out new functionality releases more quickly. Furthermore, the use of Databricks Utilities and a one-click Tableau connector in Partner Connect has simplified the process of finding insights and creating dashboards, respectively. Overall, Aktify is getting better data processing performance from a simpler technology footprint.
Quantitative Benefit
  • 80% reduction in data engineering hours, reducing costs
  • 95% reduction in time to onboard new employees
  • Six-figure annual savings in IT head count costs

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