Lead generation. Those two little words can bring a smile to a marketer’s face or make them want to tear their hair out. Why? Because it’s a complex beast with a ton of moving parts, and getting it right can feel like navigating a minefield blindfolded.

But fear not, fellow marketers! While lead gen can be tough, understanding the common challenges is the first step to conquering them. Alright, let’s get down to brass tacks and explore the common pitfalls that can trip up even the most well-intentioned lead generation campaigns. To illustrate these challenges, let’s use the following fictive scenario…

Data-Driven Delights: How GourmetGear Serves Up Hot Leads

At GourmetGear, we’re all about keeping kitchens running smoothly. We’ve become a one-stop shop for restaurants over the years, offering everything from high-tech ovens and refrigerators to fire suppression systems. We don’t just sell equipment though; we handle installation, repairs, and ongoing maintenance too.

A logo of a fictive company called GourmetGear.
The logo of our fictive business GourmetGear - a one-stop shop for restaurants.

We’re the data gurus, and we’re here to help the sales team hit their targets. They set the campaign strategy, and we provide the fuel: high-quality leads that are ready to be converted into customers.

Lead Generation From Within

Our first mission is to boost revenue from our existing customer base. Here’s the game plan dictated by the business:

  1. Service Upsell: Every fire suppression system needs regular maintenance. We’ll identify installations that aren’t currently covered by a service contract and reach out with a tailored proposal.
  2. Proactive Renewal: New environmental regulations are on the horizon, phasing out certain refrigerants. We’ll pinpoint customers using these soon-to-be-obsolete coolants and offer them a seamless upgrade to eco-friendly alternatives.

To ensure our sales team can focus their efforts effectively, we’ll enrich each lead with key information:

  • Sales History: Knowing what and how much we’ve sold to a customer helps us gauge their potential value.
  • Sales Rep Assignment: Each lead will be assigned to the appropriate sales representative based on territory, product line, or existing relationships.
  • The Right Contact: We’ll provide the best contact information for each customer, whether it’s the CEO or chef, phone number or email.

A sales & service ontology covering several objects and relationships.
This ontology is one possible representation of GourmetGear's sales and service functions. It helps us quickly pinpoint the logic needed for effective lead generation..

With our data sources mapped and our logic defined, we’re just a few SQL queries away from delivering those valuable leads.

Lead Generation with External Data

GourmetGear’s expertise in fire suppression isn’t limited to restaurant kitchens. We can protect a wide range of businesses, from offices and data centers to schools and hospitals. This opens up exciting new markets and requires a fresh perspective on our lead generation strategy.

Here’s how we’ll bring in external data to pinpoint these high-value prospects:

  • Location: We’ll tap into OpenStreetMap to identify the locations of potential customers, ensuring we’re targeting the right businesses in the right areas.
  • Customer Deep Dive: We’ll leverage external web services to obtain accurate customer information, such as revenue, number of employees, and key decision-makers (contacts).
  • Integration: We’ll route a lead to the appropriate sales rep and create a detailed record for them in our CRM system. Appropriate means, by product domain, by vertical, by geography, and taking into account capacities to not annoy our sales reps with too many leads in their mailboxes.

Pipeline consiting of OpenStreetMap data, a contacts API, and the CRM.
We subset to specific location types using OSMs tags, such as 'amenity=hospital'. Next, we use one of several paid contacts APIs to enrich our location with key decision-makers. Finally, we assign the data to a sales rep that will follow up on that lead.

Stay tuned for our upcoming articles on OpenStreetMap and contacts APIs! We’ll delve into licenses and provide practical tips on how to navigate and query data by example.

Lead Generation Roadblocks

Lead generation sounds simple in theory, but in practice, it’s a minefield of potential problems. Some obstacles are rooted in data and engineering complexities, like fragmented systems and data inconsistencies. Others can arise even with a perfectly tuned data pipeline, highlighting the need for a holistic approach that considers both technical and strategic factors.

Roadblocks From Data

As the data team, our role is to empower the business, not hinder it. So, let’s first examine how to ensure we’re operating at peak efficiency and avoid becoming a bottleneck ourselves.

  1. The Blurry Vision: GourmetGear’s story starts with a clear description of the campaign strategy. In reality, it’s a challenge for the business to define effective campaigns without a clear, consolidated view of our data landscape. How many fire suppression systems lack active service contracts? Which refrigerants are used in our installed refrigerators, and what are the viable replacements? What other opportunities should we target, and how do we justify those decisions?

The IT landscape of GourmetGear consists of several ERPs and other systems, which are linked logically.
We need to tap into a variety of data sources to get the full picture for these campaigns. Our supply chain systems hold detailed product information, while our sales and service ERPs track customer transactions. And of course, our CRM is the central hub for customer and contact details. It's a bit of a data puzzle, with some systems specific to certain product lines or regions.

Treatment: If our ambition is to be true data gurus, simply churning out leads isn’t enough. We need to provide the business with a comprehensive and easily digestible view of our sales and service operations. This means building a comprehensive data foundation – an “ontology” – that captures the relationships between our products, services, and customers. This foundation will serve as the bedrock for various data-driven initiatives, including, but not limited to, lead generation.

  1. Disconnected Data: You offer a service contract to a customer already covered. Oops! Or you target a refrigerator for a coolant swap when it’s already eco-friendly. Double oops! These blunders arise from duplicate records and broken links between systems. Inconsistent product information across databases adds to the confusion, making it tough to target the right prospects.

Installation linked with service after matching duplicate records.
We identify service upsell opportunities by identifying installation jobs from our past, which are not under contract today. This can go wrong if we have undetected duplicate records in our customer master.

Treatment: Imagine a network of interconnected data where customer records, scattered across your systems with their own unique IDs, are linked together seamlessly. Cross-reference tables act like bridges, mapping those individual IDs to a single entity ID. This ensures all records related to the same customer are connected, providing a consolidated customer view and eliminating those pesky duplicates and inconsistencies that can sabotage lead generation. Curious about entity resolution? Explore our blog to learn more!

  1. Engineering Chaos: Taming the data beast requires a multifaceted approach. We need to extract data from various sources, transform it (cross-references included), load it into different destinations, orchestrate its flow, and monitor it - and potentially more. If a simple change request sends shivers down your spine, you’ve got a problem. Without the right tools and processes, this intricate dance can quickly devolve into chaos.

Treatment: We need an analytics platform that promotes good engineering practices and fits GourmetGear’s lean operation and budget. We leverage dlt on Modal to extract data from all our sources and load it into our MotherDuck data warehouse. Transformations are organized within a dbt project, allowing us to use our preferred languages, SQL and Python, and seamlessly incorporate deduplication workflows. We orchestrate and automatically refresh our pipelines on a regular schedule with Dagster. And of course, every piece of logic is meticulously version-controlled on GitHub.

Join my mailing list and stay tuned for an upcoming blog post diving deep into this cost-effective data stack, a solution that works for 99% of companies!

Other Roadblocks

Okay, so we’ve built a solid data foundation and banished those pesky duplicates. Great job! But don’t pat yourselves on the back just yet. Lead generation still presents a few hurdles we need to clear. Let’s take a look…

  1. The CFO’s Dilemma: Shiny new tools are a dime a dozen, each promising the moon and boasting incredible ROIs. But experienced CFOs know better than to fall for slick marketing and empty promises. They need concrete evidence, not just hype.

Treatment: Begin with a targeted proof of concept, leveraging open-source tools and streamlined processes. Set up a simple development environment using a local Python environment with dlt, Dagster, DuckDB, and dbt. No need for complex scheduling or massive computing power just yet. Generate leads interactively and upload them manually to your CRM. Maintain rigorous version control with Git to ensure a smooth transition to a production environment later on. This approach allows you to demonstrate value quickly and efficiently while adhering to sound engineering principles.

  1. Expectation Hangover: You’ve championed data-driven lead generation, secured the green light for a proof of concept, and now expectations are sky-high. The business anticipates pristine data and immediate results, with every department clamoring for a piece of the action. But reality bites. You’ve got a mountain of data sources to wrangle, from a jumble of ERPs to various other systems. Your small data team is suddenly staring down the barrel of an overwhelming workload.

Treatment: Choose wisely. Focus on the most promising campaign, region, or product line, and set clear limits. Define milestones and get sign-off from the business at each stage. Be transparent about your progress, acknowledge any limitations, and maintain a pragmatic approach. The business is sick of large numbers of poor quality leads. Deliver quality first.

  1. Diminishing Returns: It’s true that lead generation often follows a boom-and-bust cycle. Initial phases yield a bumper crop of leads, followed by a steady decline as the low-hanging fruit is plucked. So why invest in a foundation when the most obvious opportunities can be seized with some shortcuts?

Number of released leads over time with a peak in a mass roll out and lower stable volumes afterwards.
The Proof-of-Concept (POC) tests the lead gen engine on a fraction of the business. If the POC succeeds, we apply the logic across the whole business, clearing out many left behinds. After that, a smaller number of new leads is released on a quasi-continuous schedule.

Treatment: Don’t let that foundational work go to waste! Lead generation is just the tip of the iceberg. Envision other initiatives that can leverage this investment and deliver even greater value. (Hint: Keep reading!)

Why Lead Gen is Just the Appetizer

If you’re struggling to generate high-quality leads, chances are your data foundation needs some serious work. Building that robust ontology on top of clean, deduplicated data is the real challenge. But here’s the thing: once a company like GourmetGear invests in that foundation, the possibilities go far beyond lead generation. It unlocks a whole menu of data-driven initiatives:

  • Pricing Power Plays: GourmetGear’s sales reps have some wiggle room on pricing, but striking the right balance is tricky. We want to maximize margins without losing deals to competitors. At the same time, we can’t win every deal with a fat margin, as our resources are limited. And sometimes, accepting a slim (or even negative) margin strategically can pave the way for more lucrative future deals, like locking in a profitable service contract after a loss-making installation.
  • Supply Chain Symphony: GourmetGear’s supply chain and sales operations often feel worlds apart. Factories operate in the dark about what’s selling, while sales teams lack visibility into upcoming inventory. The result? Bloated storage costs and delayed (or even failed) deliveries.
  • And Beyond: The potential applications are practically endless. Customer attrition, fraud detection, market analysis – a strong data foundation can fuel them all.

Of course, each new initiative might require expanding and refining that foundation. But that incremental effort pales in comparison to the heavy lifting of building the initial structure. With a solid data foundation in place, GourmetGear can unlock a world of opportunities and drive growth across the entire business.

Wrapping It Up: Lead Gen for the Long Haul

Lead generation is more than just a marketing buzzword; it’s the lifeblood of business growth. But as we’ve seen, it’s not without its challenges. From data silos and duplicates to misaligned expectations and the lure of shiny new tools, there are plenty of pitfalls that can derail your efforts.

The key takeaway? A solid data foundation is essential for effective lead generation. By investing in data quality, integration, and accessibility, you can empower your sales team with the insights they need to succeed. And remember, lead generation is just the beginning. With a robust data foundation in place, the possibilities are endless. So, embrace the challenge, learn from the pitfalls, and watch your business thrive.

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We’re here to help! Contact us today for a free consultation and let’s discuss your specific lead generation challenges.

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