Amplitude solutions partner launch

Announcing Amplitude’s Solution Partner Program

Amplitude exists to help companies build better products. Amplitude is well known for its intuitive user interface, and out of the box dashboards and reports. Yet, many companies lack the resources or experience necessary to really leverage a product analytics platform – that’s where Amplitude Solution Partners come in.

Today, we are very pleased to announce the launch of the Amplitude Solution Partner Program. The program is designed to enable agencies and consultancies to provide the highest quality strategic and/or technical support for product analytics services to their customers.

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b2b-product-analytics-strategy

Does your Enterprise Have a Clear B2B Product Analytics Strategy?

While there are hundreds of well-written articles cataloguing the latest product growth metrics and frameworks used by Consumer teams, the same can’t be said for Enterprise businesses.

True, we have seen a “consumerization” of Enterprise software over the last decade with the proliferation of freemium SAAS models making Enterprise products more and more like Consumer experiences. We have also seen consensus emerge on biz-ops strategy for B2B business models — from structuring sales contracts for higher ARRs to optimizing inbound and marketing conversion.

However, there is little consensus on how B2B product managers, analysts and growth teams should align their product metrics to drive Enterprise success. How should enterprise products define their KPI? Is it NPS and if so what if your largest paying clients have always given you low NPS scores? Is it retention and if so what does retention mean when you have annual pre-paid contracts with your clients? Is it preventing churn and if so what about high-risk customers who are very likely to see involuntary churn?

In short, what does it mean to build a better B2B product? Do we focus on what drives revenue or what drives user experience? How do we understand what exactly links these two metrics together? How do we measure what’s working when it often takes months for results to show in the form of new customers closed?

A B2B product analytics strategy is a starting place that can help us frame answers to all these great questions. There are 5 core attributes that set B2B product analytics apart . A deep understanding of these should form the core of an Enterprise product analytics strategy. I will elaborate on each attribute in articles to come but hope you find this to be a useful thought-starter!

1. User and Payer Experience

Even for a consumerized SAAS business on a month-to-month subscription model, there are different personas to optimize for. You have “Users” who largely want a regular customer experience — a tool that’s easy to learn, use, and share; offering them increasing functionality and personal productivity over time. A tool that makes them the master of their personal work universe — the user experience and account-level retention in activity is what the core product team needs to focus on.

The other key persona is the “Payer” — the payer experience must be the focus of a product growth team in Enterprise.

What does your Payer care about? How rapid is your product at demonstrating value so that they can quickly make a purchase decision? What will be resources required to implement it and onboard everyone? How will your product empower them to get the corporate approvals they need to buy it? Once purchased, how will you ensure they have control and ease around provisioning users and managing security? How will you ensure adoption velocity? These are product areas that B2B growth teams need to own and deliver on. Collectively, they can be called the “payer” experience.

2. Sales Velocity and the Purchase Cycle

B2B marketing attribution might just be one of the hardest problems to tackle in the growth analytics. Not only is it multi-touch, like in consumer businesses, but also multi-person and multi-week. Your out-of-the-box CRM platform might solve for managing the process, but so far, offers little analytical insight into how to improve it — in terms of conversion rate and sales velocity.

The implication for a product growth team is that we need to capture the changing “Payer” needs over the purchase cycle and design the right product experiences tailored to move each stage forward faster.

Some helpful questions to brainstorm for B2B product teams on velocity:

  • How can product features improve sales velocity at each stage in the GTM funnel? Have we built any “accelerators”?
  • What product features would broaden the top of the funnel?
  • What product features could overcome current bottlenecks?

3. Measuring “Feature-Customer” fit

It’s critical for B2B product and sales teams to be in perfect sync on who their target customer is and what the prospect pipeline looks like.

Often as a SAAS startup grows, there is a widening gap between the Users that the product was designed for and the Prospects that the sales executives are pitching.

This is the primary reason SAAS startups fail to cross the chasm and run out of cash somewhere between Series B and C rounds trying to grow their ACVs. Mark Leslie, the founder and CEO of Veritas covers this challenge brilliantly from the point of view of a sales team in his paper “The Enterprise Sales Learning Curve”. How should product teams measure and track their product’s fit with target customers?

For instance, if you started out as SMB software and your sales team has moved upstream, you need to invest in Enterprise Readiness. If you designed your platform for the e-commerce industry but are getting traction in fintech/healthcare instead, you need to invest heavily in Security. Such changes can make your PQLs (product qualified leads) misleading unless you are measuring product fit with target customers on an ongoing basis.

One of the best ways to achieve this is to segment your paying customers based on whether they fit the “target” customer profile your sales team is focused on and and analyze feature-wise retention and stickiness. If you have feature-customer fit, then the product areas you are planning to double down on will have higher retention and stickiness in your target customer segment.

4. Critical events — a group’s behavior pattern

The foundation of any product analytics strategy lies in identifying a critical event in your product which signals that a user got the right value out of it. For Airbnb, this is making a booking. For Snapchat, it’s perhaps adding a Snap to your Story (hard to say if you’re born before 1990).

B2B critical events tend to be far more complex — particularly if you have a professionally sold product without a freemium model.

For a professionally sold product, often the “critical” event is a recurring pattern of behavior within a group. For instance, it could be a specific set of core users being active on your platform 5 days/week. It could be a certain minimum weekly usage level that the whole account hits collaboratively. It could be the act of customer collaboration within your product itself.

For a freemium model, the critical event that signals likelihood of conversion (also correlated to PQLs) could be the velocity of initial adoption — i.e how quickly did the account get to 25 DAUs?

Identifying this complex behavior pattern that suggests a team of users is getting recurring value from your product should be a core focus for a B2B product team.

It often takes some real data spelunking to gather evidence that the “critical event” — the pattern of behavior you want to encourage — is the one that correlates the best with your long term goal — i.e., happy and growing accounts. This is my current favorite B2B analytics puzzle, so you’ll hear more on critical events for Enterprise later!

5. Churn Risk with locked-in Customers

The fact that users are often temporarily locked into an Enterprise product makes managing churn and predicting churn completely different skill sets. Particularly for companies that have month-to-month subscription plans, it’s critical for product teams to invest in churn prediction.

This entails building a deep understanding of the behavioral predictors of both voluntary and involuntary churn.

Good indicators to track include overall account-level usage dipping, lower count of critical events, power users dropping off the platform or even a lack of growth in adoption itself. Unless the product team invests in analytics to track these complex behaviors programmatically, customer success/support teams are unable to proactively prevent churn.

In summary, it’s critical for Enterprise Product teams to understand the impact that their choice of KPIs, or lack thereof, has over the rest of the company. Choosing the wrong metrics or failing to ask the right questions can slow down your organization for months and years to come.

At Amplitude, we recognize how important these nuances are for B2B customers. Most out-of-the-box analytics tools don’t address the needs of B2B customers at all — we are making a massive investment this coming quarter to change that! Amplitude already supports seamless toggling between users and accounts while tracking core KPIs. We are about to release new features to support in-depth behavioral analytics at the account level.

We are excited to help Enterprise PMs implement a strong product analytics strategy that helps grow their businesses and build better products! Watch this space! 🤓😊

March 2017 Product Update

March 2017 Product Update: Improvements to Funnels, Event Segmentation

We’re excited to announce new features and improvements since our February product update. You’ll find major improvements and information on:

  • UI/UX
    • Change projects directly from chart view
    • Search in data tables
    • Tooltips on dropdowns
    • Redesigned charts on dashboards
  • Features Improvements:
    • Funnels
    • Event Segmentation
    • Behavioral Cohorts
  • New ability to delete event types
  • Customize the ‘[Amplitude] New User’ definition (Beta)
  • Resources
    • Product Analytics Playbook: Mastering Retention
    • Webinar Series
  • SDK Updates

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Confirmation Bias product management

Confirmation Bias in Product Management (And How to Avoid It)

Confirmation bias is one of the most pervasive tendencies in human nature.

Bestselling author and professor, Michael Shermer sums up the reason why we are so susceptible to confirmation bias: “Smart people believe weird things because they are skilled at defending beliefs they arrived at for non-smart reasons.”

Confirmation bias is the human tendency to interpret new information as a confirmation of our existing beliefs and ignore it if it challenges our existing beliefs. For example, if you see a glowing object in the night sky and you’re a firm believer in UFOs, you might be convinced you’ve just spotted an alien spacecraft.

The presence of confirmation bias has been well-documented in everything from the 2016 U.S. election to scientific research. And product managing, growth hacking and analytics are definitely not immune to it. Here are some important examples of confirmation bias in product management and analytics and suggestions for how to avoid it.

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Tinybop-cover

Meet the product team that’s using data to shake up apps for kids

Remember the days when online gaming consisted of terrible design and graphics with heavily pixelated characters? Thankfully, technology has improved and those days are behind us.

Launched in 2012, Tinybop is part of a growing market of educational apps for kids. In an age where tech rules, they’ve adapted to the changing landscape to accommodate how children learn and play. Their slogan says it all: Toys for Tomorrow. Continue reading

product-analytics-playbook

Introducing the Product Analytics Playbook

The beginning of an industry

Over the past few months, we’ve posted several excerpts on the blog from a big project we’ve been working on: a comprehensive playbook for using analytics data to improve user retention. Putting together the playbook has a been a huge undertaking from many people at Amplitude. I don’t think we knew what we were signing up for when we started. After thousands of hours of work, hundreds of analyses, and working with dozens of our customers, we’re excited to finally share it with you.

Today we’re releasing the Product Analytics Playbook, Volume 1: Mastering Retention. Volume 1 is a comprehensive approach to retention across all stages of the user lifecycle. It covers how to build retention into your product. It also covers how to leverage user behavior data to identify opportunities to improve your product. Understanding and improving retention is core to long term product success and the cornerstone of using product analytics to build better products.

get the playbook here

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