(Please note: This blog is an excerpted version of our guide. Get the full guide, “Make Customer Insights Actionable with Product Usage Data” here.)
What is product usage data? How can marketing, product, sales, and support use it?
Product usage definition: Product usage data tracks what customers do with your product, when, and for how long. Insights on product use can help you upsell more and churn less because product usage data contains valuable customer insights to optimize post-sales processes, like rapid account provisioning at scale, just-in-time customer messaging, and product usage segmentation and patterns that surface customer insights on engagement and churn risk.
- For marketing
Product usage segmentation helps you send the right message at the right time to the right leads across each person’s customer journey
- For product
Product usage data helps you understand which features your customers are using most frequently and how
- For sales
Product usage data helps alert you to early upsell and cross-sell opportunities
- For support
Product usage data helps you rapidly onboard and provision new customers and prevent churn
That is...if you can get to it.
What’s preventing you from utilizing product usage data?
Most businesses’ customer data is siloed, “dark,” or otherwise inaccessible. Do you have clear, unfettered access to all your product usage and user behavior data today, in a format you can immediately use to inform what you do every quarter?
Marketers - Are you sending the right messaging to the right leads at the right time?
Product managers - Do you understand exactly what your customers are doing with your products and which new features must be prioritized?
Sales professionals - Do you know which happy customers are ready to be upsold, and when?
Support professionals - Do you know which unhappy customers are about to churn, and when?
Unfortunately, the answer is probably “no.” Here’s why.
Data overload is happening. It’s a problem.
Consider how much data is already being produced by businesses worldwide. Studies suggest global data doubles every 1.2 to 2 years, with some estimates going as high as an increase of 50x by 2020. Not all data is valuable, but research firm IDC estimates that “high-value data worth analyzing to achieve actionable intelligence will double.”
More data might not be a problem if it were usable. Unfortunately, a recent survey found that 57% of data professionals need days, if not weeks, to access essential data. Another survey polling hundreds of global business executives reports that 51% of companies feel their data is too scattered or siloed - locked up in dozens of different applications in their technology stack.
The solution: Unlock and unsilo product usage data with an integrated stack
To access the hidden value of actionable customer insights locked away in your product usage data, you need the following components:
- Data sources - All the business data you produce
Data sources provide data on different aspects of your customers’ activities. Some customer insights examples include their interactions with your product, website, and tech stack, and when and how they interact.
- Data warehouse - Where data is formatted and stored
A data warehouse is a repository of data, typically formatted in a manner to make it usable for other processes. It’s common for many businesses to use an ETL (extract, transform, and load) solution to properly cleanse and format their raw data for loading into their data warehouse.
- Data flow - Making your warehoused data actionable in your tech stack
Finally, to make your data genuinely actionable, you need the means to flow your data to a data warehouse to drive sales and marketing campaigns for revenue, as well as operations tasks to provide customer and finance support.
Solving the integrated stack puzzle
You’ve already got the tech stack you use today. You may even have, or be looking at, a data warehouse. The final piece of the puzzle flowing data freely through all your applications to centralize and take action on it, which requires an ETL and integration solution to connect your data warehouse with your stack.
Until recently, each of these critical business needs would have been handled by two separate solutions, each exclusively the domain of developers. But now, there’s a better way.
General Automation Platforms - Connect and flow app data, plus ETL
A General Automation Platform (GAP) seamlessly connects your tech stack components to your data warehouse, and can also handle ETL. It also adds an automation layer to enable users to act on crucial business data automatically. (Learn more about GAPs in “The Beginner’s Guide to General Automation Platforms.”)
GAPs perform these important functions by:
- Integrating services at the API level
A GAP interfaces with various applications at the application programming interface (API) layer - the “packaging” layer of software that enables it to talk to other apps. A GAP can integrate, or seamlessly connect, any software application to one another to unsilo your business data and flow it where you need it. Learn more in “What are APIs and API integrations?”
- Full ETL functionality with support for flat files such as CSVs
A GAP can handle ETL functions by extracting flat file data from your stack - such as taking lead lists from your marketing platform to load into your CRM. The best GAPs can kick off a fully automated ETL data cleanse and transformation with a single email. Learn more about how to kick off automated processes in “The Beginner’s Guide to Automation Triggers.”
- Ease-of-use for business users (plus flexibility and power)
A GAP isn’t just for IT. These platforms are for business users across any unit of your organization and have an easy-to-use, drag-and-drop visual interface that anyone can start using in minutes. However, the best GAPs also have a variety of useful helpers and powerful features such as conditional logic, branching processes, and loops.
We’ll wrap up with some of the specific, actionable use cases for product usage data you can build with a General Automation Platform.
Learn how to build these use cases, with full diagrams and walk-throughs, in the full guide.
Use case: Rapid account provisioning
Automated account provisioning at scale is an increasingly crucial use case, particularly for direct-to-consumer businesses that seek to not only add new customers to their customer pool but also to then continuously re-engage them for repeat business.
Using a General Automation Platform, you can integrate your payment processing solution, CRM, data warehouse, and even marketing platforms to create a fully automated account provisioning process to surface these important customer insights:
- Integrate payment platform - Connect any transaction, including a credit card swipe, to the rest of your tech stack to initiate the account provisioning process
- Verify customer data in CRM - Automatically route payment data to your CRM for verification of a new customer account (or to update an existing account)
- Send a contextually appropriate customer email - Automatically deploy a “Welcome aboard” email to new customers or a “Welcome back” email to returning customers
- Place the customer into an appropriate follow-up marketing program - Once you’ve verified this customer’s status, place them into the corresponding campaign
Use case: Just-in-time messaging across the customer journey
A significant concern for both direct-to-customer and B2B firms is appropriate messaging at every stage of the customer journey. By utilizing product usage data, companies can rapidly identify customers by stage and usage patterns.
With the help of a General Automation Platform, you can integrate applications such as your CRM, customer data platform, lead enrichment, data warehouse, and marketing platform to rapidly deploy messaging appropriate to customers at any stage in their journey:
- Capture product interaction and confirm customer status in CRM - Tracking customer activity, such as via webhook, confirm customer status in your CRM.
- Request persona from customer data platform - This integrated process then calls its customer data platform to add any relevant persona data on file.
- Enrich data as needed - The process then calls its lead enrichment solution to enrich any missing contact information for this customer.
- Update data warehouse - The process then updates the customer’s status in your data warehouse.
- Call email metadata + custom follow-up - Finally, the process pulls email metadata from its customer data platform and sends just-in-time follow-up via marketing platform.
Use case: Prevent churn and gauging upsell potential
Losing customers to churn not only means losing recurring revenue, but also a higher burden from ongoing customer acquisition cost as your company must replace churned customers. Conversely, having happy customers means more opportunities for upselling (upgrading customers to higher-priced tiers), expansion (growing billable customer usage), and reactivation (renewing existing customers). Research suggests that retaining customers can be 5-7x cheaper than acquiring new customers.
A General Automation Platform can manage all these processes by connecting data warehouse and user analytics to determine whether engagement patterns are as expected, then running a series of follow-up automated processes incorporating helpdesk, CRM, project management, internal chat alerts, and marketing automation to trigger the appropriate follow-up.
- Initial process: Regular account health check - Using a calendarized reminder, this process regularly runs an account health check at prescribed intervals.
- Data warehouse + user analytics call - Making calls to your data warehouse and user analytics, the process pulls up product usage levels to determine if usage is above or below average.
- Churn risk follow-up - For at-risk accounts showing abnormally low usage, this process can call up follow-up steps such as:
- Updating customer account in CRM and helpdesk as “at-risk”
- Kick off retention-related tasks in project management software
- Kick off retention-related marketing nurture sequences, including relevant content such as surveys, renewal discounts, etc.
- Expanded usage follow-up - For accounts with abnormally high usage that might be amenable to cross-sell or upsell, this process can call follow-up steps such as:
- Updating customer account in CRM as “potentially ready for upsell”
- Send an automated internal chat alert to the sales owner(s) of the account
- Kick off upsell-related marketing nurture sequences, including relevant content such as how-to guides, upgrade discounts, etc.
Retaining existing customers can cost up to 5-7x less than acquiring new ones. Image courtesy Forentrepreneurs.com
Use case: Score free trial leads using product usage data for sales
Your happiest enterprise customers are often ones that grow organically from previous usage of your product, whether from an existing account or a free trial. Identifying these accounts early and ensuring they get the attention they need from your sales team can accelerate their growth, happiness, and loyalty—all critical ingredients for retention and revenue. But it can be tricky to manage all the moving parts so you can responsively and confidently score and identify the self-service or trial accounts that qualify to speak to a sales rep, particularly if your product and customer-facing teams work in different tools.
- Capture product usage data across your marketing stack: Track all customer product activity and usage, either by webhook or a customer data platform like Segment.
- Identify other lead data that demonstrates intent to buy: Identify other lead data such as role, vertical, or company size.
- Generate lead score: The exact calculation of the lead score depends on your company’s needs. It can be as simple as adding positive intent attributes (like a product usage threshold) and subtracting low intent attributes (like viewing your jobs page). Here is an example to get you started.
- Append scores to your CRM: Since many companies use their CRM as a system of record, it’s essential to have the CRM upserted here. Now your sales rep can see which lead has a high intent score and prioritize outreach to them first.
Now that we’ve covered some ideas let’s explore some actual use cases that product and revenue teams are already using to grow product engagement and revenue and prevent customer churn.
New Relic uses product usage data to 6x engagement
New Relic is a software analytics leads whose platform provides real-time insights to help technology companies improve their software deployment process. Like many rapidly growing software-as-a-service (SaaS) companies, New Relic has customers of a wide variety of sizes, from startups of fewer than ten individuals to Fortune 100 companies. Additionally, having a suite of enterprise products means juggling a multitude of users across different lifecycle stages. For instance, some customer insights examples included knowing not just job titles, but also customer stage across pre-sales or post-sales cycles. Having such a diverse set of customers with ever-changing needs created a unique challenge for its growth team.
Challenge 1: Personalizing multi-channel messaging at scale
Different users in different roles at companies of various sizes tend to have different needs and goals at any given time, which means one-size-fits-all marketing messaging will mostly fail to serve every type of customer. Also, every customer is at a different point in the customer lifecycle. Some require pre-sales education, while others need post-sales onboarding. New Relic identified an opportunity to grow engagement with customization across both multiple personas and lifecycle stages. For example, a back-end engineer getting started with New Relic would be more likely to want to learn more about the platform’s features, while a CTO power user would be more receptive to product updates specific to their business needs.
Solution: Using a GAP to connect customer data and messaging platforms
Using a GAP, New Relic connected product usage data from Segment to Salesforce to identify customer lifecycle stage and persona and update records within CRM. The GAP then bidirectionally syncs customer updates with Intercom, which the company uses to interact with users in all customer lifecycle stages. New Relic uses a GAP to build an automated workflow to handle data flow and syncing to ensure dynamic, persona-based and lifecycle-based cohort updates in Intercom and by email.
Result: New Relic doubles open rates and increases clickthrough rates by 600%
Senior Director of Self-Serve Business Niels Fogt explains, “By connecting our growth stack, we personalized messaging at scale for hundreds of customers and doubled our engagement rates.”
Challenge 2: Anticipating and preventing churn risk
New Relic identified a correlation between product usage patterns and customer churn. Specifically, the company’s growth team found a leading indicator: Accounts using very little of their allotted usage limits tended to be a churn risk. Whenever the company identified an account with potential churn risk, its customer teams would engage with those accounts to prevent churn. However, this process was manual and reactive at best.
Solution: Using a GAP to connect customer data from Segment to monitor product usage
New Relic used a GAP to sync product usage data from Segment, as well as account usage limits, to send automatic alerts to its customer success teams via Slack and email. The company now uses this new information to reach out to at-risk accounts to prevent churn proactively. “By monitoring product usage data for our enterprise accounts, we can see which ones are actually consuming their entitlement allowance,” explains Fogt.
Result: New Relic reduces enterprise churn risk
Using a GAP to connect product usage data on the back-end to real-time alerts for the customer success team on the front-end has helped New Relic get ahead of churn risk. Fogt comments, “Accounts that aren’t consuming their allowance may be churn risks, which we can proactively address on the support side. Accounts that are consuming significant amounts of their allowance are potential upsell opportunities. All these insights help us drive more revenue and growth across all customer segments, not just smaller accounts.”
Learn more about how New Relic uses a GAP in the customer success story.
New Relic flows aggregate customer data and CRM records through data warehouse to customize messaging for any persona in any lifecycle stage.
DigitalOcean drives hyper-personalization for marketing with product usage data
Cloud computing leader DigitalOcean is experiencing rapid growth, thanks in no small part to the ingenuity of the company’s marketing team. Like most modern, customer-facing organizations, the company uses a variety of software tools, including Salesforce for sales, Marketo for marketing automation, a customer service ticketing solution, and an analytics tool for measuring product usage and customer behavior. Unfortunately, customer and product usage data were siloed across multiple apps, which made it challenging to deliver a holistic and personalized marketing experience that would drive higher engagement.
Challenge: Reactive marketing messaging not informed by customer data
DigitalOcean’s marketing team’s campaign strategy was limited to the data siloed in each tool. Andy Hattemer, Senior Developer Marketing Manager, explains, “In the past, our marketing was more reactive and old school. We’d go and look for an audience, and send a wave of messages.”
Solution: Stream product usage data for just-in-time, personalized marketing
DigitalOcean used a GAP to connect Segment’s product usage data with Marketo. As a result, it was able to plug customer insights directly into its marketing campaigns to make them proactive and personalized based on specific user behavior. Hattemer explains that his team now uses a GAP to run “a workflow where prospects and customers are getting the right message at the right time as they interact with our platform and our marketing.”
Utilizing product usage data gives you full visibility into your customers’ usage patterns across the entire customer journey, from onboarding to ongoing customer health, and gives you a powerful advantage to fight churn, as well as to retain and expand your most important customer accounts.
Get complete diagrams and step-by-step walk-throughs of each use case in the full guide, “Make Customer Insights Actionable with Product Usage Data” here.
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