Case Study

DataBees helps Duda (EMEA) filter prospects and focus on their ICP

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Felix Dandrea

Digital & Growth Strategy Leader

Company:

Duda empowers companies to create scalable, feature-rich, responsive websites optimized for fast loading and excellent out-of-the-box SEO. Over 1 million live sites are powered by the Duda platform. Duda serves companies worldwide across four main verticals: Digital Marketing Agencies, SaaS companies, local listing companies, and hosting companies. Their GTM perspective addresses a vast Total Addressable Market (TAM).

Industry:

Website Builders

Use case:

Manual lead research

Workflow:

Lead research on a budget

Introduction

Anna (Duda’s dedicated CSM) is great. She constantly ensures good data quality, stays on top of our requirements, and executes our instructions to the letter. We appreciate how proactive she is. For example, we’ll send over new instruction updates, and the following day, she’ll inform me that these changes are in place and being implemented.”

Introduction

Felix Dandrea is the EMEA Strategic Sales Manager at Duda, the leading white-label website builder for Agencies and SaaS platforms who leverage the platform to build the best-performing websites for their clients.

Felix is a revenue leader passionate about building business processes to maximize MRR, ARR, opportunity quality, and consistent sales pipelines. His team’s primary focus is generating as much pipeline and revenue as possible in the EMEA region.

Read on to discover how they leverage DataBees to fuel their go-to-market (GTM) function with high-quality lead data.

The Challenge

As a leader in the newly created EMEA team, Felix was tasked with driving regional business, creating pipeline, and generating revenue. The major hurdle he faced in these early phases was that its Total Addressable Market (TAM) was large and cumbersome, meaning their team spent a lot of time and resources collecting and filtering account and customer data points.

To tackle this large market full of opportunities, Duda would obtain lists fitting their customer profile and enrich them with account and contact data. They added these prospects to their CRM and contacted them via various outbound strategies.

Using this strategy over time, Felix realized it cast their net far too broadly, and this sales cadence included too many low-quality opportunities and bad-fit prospects.

Going back to their data sources, Felix revisited the contact lists Duda was using. He noticed they needed to improve their filtering efforts and only import a higher percentage of good-fit customers matching their ICP. This meant they knew all their outbound efforts were directed at customers who would find value in their product.

The only drawback was that Felix knew filtering the lists would be manual and time-consuming, and he didn’t want his AEs to be distracted from their existing sales tasks.

The Solution

Working with DataBees for 30+ months, Duda uses our researchers as their BDR team, filtering out bad-fit opportunities and curating ready-to-import lists based on precise ICP characteristics and attributes. Felix and his team then score and import the lists into their CRM.

Why Duda loves DataBees

No need to hire BDRs: DataBees fulfills crucial research and enrichment tasks, saving the EMEA team resources by eliminating the need for in-house BDRs. With the average BDR in the region costing $50k base plus commission, this is a significant saving.

We act as the quality filter: DataBees does the hard manual work of discovering, researching, and enriching ICP-focused prospect lists to send to Duda. AEs no longer waste time researching bad-fit customers; instead, they now spend their valuable time reaching out to best-fit accounts and booking meetings.

We provide dedicated support and hands-on service: Working directly with his Customer Success Manager, Felix can devise and execute various experiments testing out new ICP criteria and broadening their scope. This level of service allows Duda to test multiple ICP verticals and uncover new pipeline sources

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