What Growth Hackers Get Right: How to Use Customer Data

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Posted on November 10, 2020

Growth hackers use data for more than a dashboard—they use it to understand the real people behind digital products

“Growth hacker” is more than a buzzword. They’re product/marketing hybrids who have learned how to capture and read customer data in real time. And despite startups like Airbnb, Uber, Instagram, and LinkedIn using growth hacking to achieve unicorn status, established companies have yet to catch on.

In more than 20 years as a consultant helping businesses achieve digital transformation, I’ve noticed that successful growth hackers approach customer data in a radically different way than legacy enterprise businesses. They look for the real humans behind digital data signals, use modern product intelligence tools that are purpose-built for analyzing customer behavior, deploy data insights for customer activation, and treat data as a team sport.

The growth hacker mindset, combined with the right tools and practices, offers a blueprint for enterprise companies to realize digital transformation and unlock growth.

Foster Empathy Through Event-Based Data

Growth hackers understand how a nuanced understanding of customer data builds empathy. Being familiar with your customers’ wants and needs, as presented through data, helps you build better products.

Start with the mindset that data is a conduit for human interaction. Look at your data as the expression of individual people, not as anonymous masses. This mindset will help you uncover behavioral insights within your customer data and build empathy at scale.

Of course, you need more than a mindset—you also need to track the right kind of data. Old-school analytics products like Google Analytics and Adobe don’t easily track data that lends itself to understanding granular human behavior. They mostly track web activity in a dashboard. But looking at large-scale numbers like pageviews and purchases tends to erase the individuals behind the data. After all, pageviews don’t buy products—people do. People don’t interact with products in “sessions”: We interact with products over extended periods of time and through a variety of different channels.

Being familiar with your customers’ wants and needs, as presented through data, helps you build better products.

Instead, growth hackers look at event-based data. Event-based data tracks subtler interactions—every mouse click, keystroke, and finger swipe. When these events are analyzed in near real time with product intelligence tools, you can begin to uncover the nuances of customers’ behavior and understand their needs. This understanding, in turn, leads to better products.

Though legacy analytics tools like Google and Adobe have technically extended their platforms to incorporate events, they’re still webpage-centric at heart. Using these tools to track events remains clunky.

Use Modern Tools Purpose-Built for Customer Data

Traditional web analytics tools weren’t originally designed for customer behavior analytics. They excel at measuring anonymous webpage views at a single point in time, but not the way real people actually use digital products. Growth hackers use tools that can properly analyze complex customer data. At a minimum, such tools should accomplish three things:

  • Track interactions from multiple channels
  • Identify the same customer across sources and unify their data (called identity resolution)
  • Blend anonymous data with known customer data after customers identify themselves

Customer Data Platforms (CDPs) like Segment and product intelligence tools like Amplitude were purpose-built to achieve these goals. Segment, for example, ingests customer event data from dozens of sources (including custom ones). It then creates a unified customer profile that persists over time.

Amplitude can be used downstream from Segment to ingest events that have been unified through a CDP. It then provides data analysis suitable for both technical and non-technical users to interrogate customer metrics like retention, conversion, and cohort behavior. Amplitude also has its own identity resolution capabilities and pre-built integrations for dozens of data sources.

The advantage of tools purpose-built for customer data (not web analytics or generic data lakes) is that they were made with humans in mind. That means they provide rich, customer-oriented features out of the box, like identity resolution, privacy safeguards, and customer lifecycle reporting.

Increasingly, these tools offer pre-built predictive attributes, such as likelihood to churn, propensity to buy, and automated segmentation. Building this type of functionality from scratch takes even the largest companies years because it relies on machine learning, which is complex and expensive to spin up. Amplitude’s AutoML capabilities can automatically cluster customers based on their behavior. This allows product managers and marketers to quickly group users based on how they actually interact with the product, rather than manually creating rules based on how they think users should be segmented.

Amplitude now also offers Predictive Cohorts, which uses machine learning to segment users based on how likely they are to perform a given action. When these cohorts are applied to marketing campaigns, growth hackers can become veritable citizen data scientists.

Act Quickly on Data Insights for Direct Activation

Dashboards are certainly useful for visualizing and interpreting data analysis, but they shouldn’t be the end of the data road. And waiting on executives to make decisions based on them can take weeks or even quarters. That’s because dashboards can only point you in a general direction—it’s up to you to interpret the data and take action.

Growth hackers approach customer data in a radically different way than legacy enterprise businesses.

Growth hackers don’t have that kind of time. They take the insights they gained from their product intelligence tools and feed them directly into their marketing and engagement campaigns. That means tailoring their customer messaging based on the unique characteristics and cohorts they discovered in their data. Amplitude has pre-built connectors that can trigger this communication in real time—no waiting on a dashboard.

For example, if an analysis identifies a group of customers who are likely churn, the obvious next step is to send them an email or mobile push notification to help keep them in the fold. By triggering this messaging automatically, growth hackers get to change the customer experience at lightning speed.

Make Data a Team Sport

The final secret of growth hackers? They work as a data democracy—as a team that collaborates with data to discover new ways to serve their customers. Data isn’t siloed to a small group of highly technical users—it’s easily accessible to growth-hacking product managers, marketers, and designers as well. Everyone has self-serve access to dig into the data to validate growth hypotheses, identify friction points, and observe customer behavior.

If data experts are the gatekeepers of customer insights, then a company’s ability to learn and adapt quickly is bottlenecked by the bandwidth and expertise of a limited few. Google Analytics and Adobe are challenging for non-data experts to explore beyond surface-level insights. When technical folks just create dashboards to communicate the data analysis to other team members, those non-technical users can’t interact with and ask questions about the data. And asking the engineering team to answer those questions for them just slows everyone down.

Modern analytics platforms like Amplitude are designed from the ground up to be used by non-data-experts. Amplitude’s UI employs natural language and a point-and-click interface for building queries. It avoids the use of obtuse, platform-specific terminology. You won’t see strange terms like eVars, sProps, or goal slot IDs.

Amplitude also provides a wide range of pre-made, high-value, easy-to-configure charts, making it effortless to start exploring customer behavior out of the gate. Finally, Amplitude offers a host of team collaboration features, allowing growth teams to add comments to charts, publish their analysis, and discuss data within the tool itself.

By truly democratizing data, organizations that embrace growth hacking can radically shorten feedback loops. This allows them to execute significantly more growth improvements than their traditionally minded competitors.

Become a Growth Hacker

Do you need to discard your existing data analytics tools like Google Analytics, Adobe Analytics, data warehouses, data lakes, and traditional dashboards? No. Just use them for the purposes they were built for: web analytics, data storage, and visualization. When it comes to driving growth through rapid experimentation and optimization, use modern product intelligence tools to achieve your desired results. Combined with a growth hacker’s customer empathy, ingenuity, and collaboration, you, too, can see that coveted hockey stick growth.

A version of this article originally appeared on Medium.

Jake Bennett

Jake Bennett is a practice area lead at Slalom, specializing in MarTech architecture and customer data. With 20+ years of consulting and agency experience, Jake has worked with a broad range of clients across industries, from startups to Fortune 100 companies. His primary focus is helping companies leverage data for analytics and personalization to create high-performing digital experiences.

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