3 Data Strategies to Sell to Developers

Understanding the Challenges of Marketing to Developers

Developers represent a uniquely discerning audience. Traditional marketing approaches often prove ineffective, as they generally prefer recommendations from peers over direct sales pitches.

Consequently, numerous software companies have experienced repeated campaign failures, leading some executives to question the value of all sales and marketing endeavors.

Why Selling to Developers Differs

However, marketing to developers isn't inherently impossible; it simply presents distinct challenges. A successful strategy necessitates a careful balance between cultivating a robust organic marketing function and delivering the appropriate message to developers at each stage of their buyer journey.

Achieving this balance can be complex.

A common obstacle marketers face is a lack of adequate data and measurement tools to accurately assess the impact of their initiatives on business outcomes.

The Power of Organic Marketing

Marketers, community managers, and developer relations professionals often find the greatest success with organic marketing strategies. However, this approach is notoriously difficult to quantify.

Organic marketing encompasses investments in channels such as referrals, organic search, organic social media (community building), and direct website traffic (brand recognition). Activities like paid advertising, banner ads, events, and direct sales efforts are excluded from this definition.

The effectiveness of organic efforts is best measured using a metric known as the Natural Rate of Growth.

The Increasing Complexity of Attribution

In today’s digital landscape, with its numerous touchpoints, determining which channels initially introduce users to a brand is becoming increasingly difficult.

This has fueled the rapid adoption of platforms like Orbit, Tribe, and Mighty, which aim to address this challenge.

While these tools offer valuable benefits, they don’t fully resolve the underlying data strategy issues that many developer-focused software companies encounter.

The following recommendations can help teams prioritize essential tasks and distinguish them from less critical ones, ultimately streamlining the process of engaging with developers.

Key Strategies for Success

Prioritize Data as a Product: Treat data as a core product, with the go-to-market team serving as a primary end user.
Map the Customer Journey: Thoroughly map the customer’s journey, from initial discovery through to expansion, and meticulously track progress at each stage.
Embrace Simplicity: Avoid overcomplicating the process; focus on essential elements.

Regarding Data as a Core Product Offering

Many exceptionally talented individuals within the technology sector have ventured into entrepreneurship, developing software solutions to address genuine market needs. While proficient in development, they often lack expertise in evaluating their creation from a business perspective.

Specifically, they possess a strong understanding of the elements that contribute to a positive user experience, but struggle with effectively conveying this value or quantifying its impact.

Typically, these organizations rely on analytics derived from a production database – or a replica thereof – which is fundamentally engineered to operate the product itself. Consequently, the data outputs and metrics do not correlate with the objectives of the marketing and sales departments.

Data linkage to customer relationship management (CRM) systems is commonly achieved through the utilization of account names or primary email addresses.

This approach frequently results in a disorganized and inefficient system. Avoid replicating this scenario.

Initiate discussions with leadership and operations personnel within the revenue-generating teams. Determine the specific product data they require, explore potential applications – both immediate and future – and establish a clear definition of data-informed decision-making.

Assign a product manager to oversee this initiative, creating a minimum viable product (MVP) and a corresponding development roadmap. Allocate between 10% and 20% of available resources to the initial implementation and ongoing maintenance of this system.

Providing the go-to-market team with access to data presented in a readily understandable format – encompassing actual users, their product utilization patterns, and longitudinal cohorts for analysis – will foster improved alignment during subsequent roadmap planning sessions.

Here's a breakdown of the benefits:

Enhanced alignment between product and revenue teams.
More informed decision-making based on concrete data.
Improved understanding of user behavior and long-term trends.
A more effective go-to-market strategy.

Understanding the Customer Experience

Ideally, at this stage, all aspects of your product should be instrumented for tracking. A significant issue arises when a compelling new feature is launched, yet its usage remains unquantifiable.

Gaining insight into user interaction with your software is valuable, but truly understanding the path a user took to find you, their evaluation process, and their eventual realization of your product’s benefits is even more impactful.

While a portion of this understanding comes from server-side product analytics, the remainder relies on tools frequently underestimated by founders with a technical background. This refers to the continued relevance of Google Analytics.

Frequently, Google Analytics provides data regarding content performance, identifying what resonates with audiences and what requires refinement. It’s surprising how many organizations lack a solid grasp of SEO principles and Google’s algorithms, leading them to disregard this crucial data source.

Analyzing this data allows for informed decisions about content strategy and optimization.

Mapping the Customer Journey

To effectively map the customer journey, consider these key stages:

Awareness: How do potential customers first learn about your product?
Consideration: What factors influence their decision to evaluate your solution?
Decision: What ultimately leads them to choose your product?
Value Realization: How do they experience the benefits of using your product?

Tracking metrics at each stage is essential for identifying areas for improvement.

Understanding these stages allows for targeted marketing and product development efforts.

The Role of Google Analytics

Google Analytics provides valuable insights into:

Traffic Sources: Identifying where your visitors are coming from.
User Behavior: Analyzing how users interact with your website.
Conversion Rates: Measuring the effectiveness of your calls to action.
Content Performance: Determining which content is most engaging.

Leveraging these insights can significantly enhance your marketing and SEO strategies.

Keeping Data Analysis Focused

A highly effective product leader shared a perspective that resonated deeply. Fareed Mosavat, previously leading product development at Slack, posits that organizations should concentrate their product tracking on only five to ten key events. This assertion was initially surprising, given my background as a data specialist.

However, upon further reflection, the wisdom became clear. I’ve observed numerous early-stage businesses accumulating substantial datasets, believing a machine learning expert was essential for interpretation. These were B2B ventures, serving a customer base of 50 or more – not large-scale social platforms.

Mosavat’s point is valid: simplicity is paramount. Allow the typical customer’s path through your product to dictate your tracking strategy, supplemented by insights from your marketing and sales teams. A wealth of readily available technology exists to facilitate this process, alongside thriving professional networks offering valuable experience.

The primary obstacle is often a mindset shift regarding the application of data to customer engagement. Consider the positive impact of delivering the correct message at the optimal moment. Doesn't it enhance the user experience when a company anticipates a challenge or highlights a previously unknown feature?

These are the experiences I value, and I advocate for more software companies to prioritize them. Achieving this requires a strategic and focused approach to data utilization.