Taking a Retrieval-Augmented Generation (RAG) solution from demo to full-scale production is a long and…
Data Strategy and Integration in Go-to-Market (GTM) Strategy
Background
When you think of Data Integration, you often think of Data Engineering, Data Science, AI or Data Analyst teams. However, Marketing Ops, Sales Ops, Rev Ops and GTM teams also frequently face the challenge of integrating external data sources.
In 2024, the average enterprise marketing team used 12 to 30 different software technologies. As pressure to build a sales pipeline and identify high-potential accounts increases, the martech landscape continues to grow in complexity.
To add to this, each new technology adds yet another data source, format and schema because most solutions aim to centralize and lock users into their data as the source of truth. This leaves marketers and GTM teams struggling to connect data across all these disparate technologies. This hinders their ability to deliver timely, relevant information to teams such as sales, customer success, or finance or even determine their own ROI.
The Challenge
A common pain point for marketers is the adoption of intent tools and related technologies. Marketers often invest in these tools and technologies to uncover new accounts and opportunities through intelligent data. However, the effort falls flat when it’s time to convince sales to pursue these accounts, align on joint campaigns, and create targeted outreach.
The result? Poor adoption and no impact.
Why do these strategies fail? In 8 out of 10 cases, it’s due to a poor data strategy and lack of ability to connect data sources.
Sellers need time to focus on selling. They rely on actionable data, which includes contact information, accounts to be present in CRM with scores and activity history, and timely notifications when important activities occur in the account. They can’t afford to waste time navigating multiple systems to decipher different data formats and then zero in on potential accounts to pursue. The opportunity cost is simply too high.
Marketers on the other hand, struggle to gain insights from multiple data sources and can’t correlate how their efforts translate into real opportunities, accelerate existing ones, or improve customer engagement. Without the ability to demonstrate ROI, marketing budgets are often questioned and are the first to be cut, increasing pressure on marketers to deliver even more with less.
The Solution
The crux of the issue is a disjointed data strategy. As technology stacks grow, so does data complexity and data chaos. Today, marketing data exists in various formats – both structured and unstructured – spread across numerous systems, shared drives, cloud platforms, and tools and technologies that often fail to communicate with each other. Some systems allow data extraction via batch processes, while others use API or real-time streaming.
The same data from multiple sources needs to be packaged to serve different needs. Marketers need it to inform advertising and bidding decisions, while they may need to share non-PII data with partners who execute campaigns on their behalf. Sales teams require it in the CRM to create and drive opportunities, and data analyst and ops teams need it in the data warehouse for revenue, pipeline, and ROI analysis.
To achieve success with your GTM strategy, you need a solid data strategy and technology vendor that offers a metadata-driven data integration platform. This platform should handle data from different systems –whether on-premise, in the cloud, or on internal drives – support multiple integration styles and create data products that can be shared with internal and external teams in a secure and compliant way and enable different use cases from analytics, to operational GTM to GenAI use cases.
If you are interested in learning how we align our GTM efforts at Nexla and demonstrate ROI, request a custom demo.
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