プロダクト主導のカスタマーサクセスチームが使うKPI

Product-led organizations are data-driven organizations. And one of their greatest strengths is that they share and democratize data so that teams across the company feel empowered to take action, too. While all of this data—product analytics, in-app messaging engagement, user journeys, feedback—is relevant for stakeholders across the organization, it’s important to examine it through the lens of how it helps specific teams drive business success and better product experiences. 

ここでは、優れたカスタマーサクセスチームが測定する上位8つのKPI（重要業績評価指標）、それらがCSM（カスタマーサクセスマネージャー）にとって重要である理由、そしてプロダクト主導の強力な組織の構築にどのように貢献しているかをご紹介します。

1. Time to value（価値実現までの時間）

Time to value measures the time it takes for a customer to derive value from your product, from the moment they start using it. This is often called the “aha” moment—when the user grasps why they need the product and understands how it will benefit them. Time to value can be measured using product analytics—specifically how long it takes users to engage with the most important features of your product. It’s a useful measure of customer satisfaction and a great early indicator of retention (or conversely, churn) for CS teams.

Time to Valueデータに対して行動を起こす方法

• For users with high time to value:
  If users don’t have a good first impression of a product and are struggling to use its key features, it’s unlikely that they will return. Dig into the behaviors of the users who are taking the longest time to engage with your product’s key features to see where they’re getting stuck. You might be able to take those findings to the product team and work with them to improve the product’s user interface (UI) or functionality, or perhaps deploy a tooltip or walkthrough to direct these users to the areas of the product they’re currently missing but should be using.
• For users with low time to value:
  The users getting to that “aha” moment the fastest are a goldmine of good behaviors. Take a look at their journey through your product and see how you might replicate their workflows across your other customers. Create in-app onboarding programs to guide struggling users through the steps your most successful users are taking.

2. 定着化

At its core, the most important function of CS is to help customers get what they need out of the products they’ve invested in, so that they can use them to achieve their goals. A clear way to assess whether customers and users are getting value from the product is to track their adoption, or the number of users or accounts who are interacting with the product (product adoption) or specific features within it (feature adoption).

Product adoption can be expressed over time by the number of monthly active users (MAU), weekly active users (WAU), or daily active users (DAU); or as a rate relative to new user signups for a given period of time. Feature adoption tracks specific features within the product so you can understand who is making use of them, and when. Additionally, closely monitoring adoption at both the user and account level helps CSMs understand which customers are seeing value from the product, which might be struggling or need a little extra help, or which might be at risk of churning—so they can intervene as appropriate. Adoption is also an effective early indicator of overall brand satisfaction and a customer’s intent to renew.

定着率データに対して行動を起こす方法

• For accounts with low feature adoption:
  Target users who have not yet adopted key features with in-app guides featuring videos or GIFs that demonstrate how to use them. This will help address enablement gaps and encourage those users to utilize the product for its intended purpose.
• For accounts with lagging or diminishing product adoption:
  Proactively reach out to customers whose adoption is trending downward to understand their challenges, inform them of new or soon-to-be released features with in-app guides, or set up a meeting to realign on how the product can help them achieve their goals.
• For users with excellent product and feature adoption:
  Launch a congratulatory in-app guide to celebrate the progress they’ve made, and ask for a review or feedback on what they love most about the product.

3. 粘着性

粘着性は、どれだけのユーザーが定期的にプロダクトに戻ってきているかを測定するもので、毎日使う月間ユーザー数（DAU/MAU）、毎日使う週間ユーザー数（DAU/WAU）、毎週使う月間ユーザー数（WAU/MAU）の3種類の方法で追跡できます。比率には、プロダクトにとって理想的なエンゲージメントの形を反映する必要があります。たとえば、医師向けの電子記録管理プラットフォームのようにユーザーが日常的に利用する必要があるプラットフォームなのか、個人向けの納税計画・申告アプリのように利用頻度が低くても季節的に利用する必要があるプラットフォームなのか、などを検討します。 

粘着性は、定着率と同様に、どれだけのユーザーがプロダクトに価値を見出し、期待するワークフローに組み込んでいるかを示すものであり、CSチームにとって貴重なものです。CSMは、粘着性を手がかりとして、「パワーユーザー」と同じ行動を顧客全員が取れるよう監視し、奨励することができます。

粘着性データに対して行動を起こす方法

• For accounts with low stickiness:
  This could be a signal that additional enablement or guidance is needed, because users aren’t using the product at a frequency or in ways that deliver the most value. Target these users with emails to encourage them to revisit the product, then serve them onboarding-style walkthroughs that guide them through key functionality when they do return the product.

• For accounts with high stickiness:
  Examine the behaviors of the users and customers leveraging the product at the highest frequencies, then build resources (like training sessions or in-app FAQs) to help other users achieve the same success.

4. 成長（グロース）

成長率は、ユーザーの獲得とリテンション施策に対する正味の効果を測定します。これは、特定の期間にプロダクトの使用開始、維持、および離脱をしたユーザーの数を捕捉することにより、新しいアカウントの追加と既存のアカウントによる使用量の増加の両方を示します。 

In general, CS teams are responsible for customer retention and expansion within their organization. Growth is a “north star” metric that gives CSMs a clear line of sight into how customers and users perceive the value and efficacy of the product. And when it’s evaluated alongside other product analytics data, feature releases, or qualitative feedback, it can be a valuable starting point for understanding what customers and users really want or need. CSMs can then take this information back to the product team to help inform the roadmap and guide the future direction of the product.

成長データに対して行動を起こす方法

• If user growth increases following the announcement or release of a key feature:
  You could infer that the feature—and potentially others related to it—are highly desired, and thus more likely to be broadly adopted. This is valuable information for the product team, and also arms CSMs with valuable proof points to bring into conversations with at-risk or low-adopting customers, in an effort to encourage them to try the new feature for themselves.
• If growth is stagnant following a release:
  This could signal a lack of awareness about the new feature. Work with the marketing team to deploy promotional in-app guides encouraging users who haven’t engaged with the feature to explore it for themselves, or to ask them what other features they may want to see in the future.

5. プロダクトエンゲージメントスコア（PES）

The Product Engagement Score (PES) is a composite metric, representing the product’s average adoption, stickiness, and growth rates. PES is intended to serve as a single, overarching metric to measure how users or customers are engaging with the product, and can be used to measure success at either the visitor or account level. If your product is only used by individuals (and not teams), then you’ll likely only want to measure each PES component at the visitor level. But if your company is focused on new logo acquisition, measuring growth (and overall PES) at the account level is best. 

For CS teams, tracking PES over time and comparing it against things like company news and product changes is a good way to compare customer satisfaction and feature efficacy. And similar to more generally used metrics like Net Promoter Score (NPS) or Customer Satisfaction (CSAT), PES is another tool CSMs can have in their arsenal to measure and monitor overall account health over time.

PESデータに対して行動を起こす方法

• PESを長期にわたって監視し、定期的に（たとえば、毎月の顧客との定例会議時）報告して、傾向と改善すべき領域を特定します。3つの指標をそれぞれ掘り下げて、前月比でPESの総合スコアにどのような影響があったのか、またその理由は何なのかを探ります。
• 四半期ごとのビジネスレビュー（QBR）やその他のエグゼクティブミーティングでPESについて報告し、プロダクトのパフォーマンスを一目で把握できるようにします。

6. 定着率と売上維持率（NRR）

Retention measures the percentage of users (or customer accounts) still using your product after they initially install or start using it, at both the app and feature level. This metric tells you how many users or customers continue using a product or feature during a given time period, and is a good indicator of churn risk. It’s an important measure for CS teams, in particular, because it’s generally operationally less expensive to retain current customers than it is to acquire new ones. In other words, low retention can cause an organization to lose money when they sign a new customer—so it’s important to work hard to drive reliable retention by delivering a great product experience, and to understand (and mitigate) the factors that contribute to a poor product experience.

Net revenue retention (NRR) is related. It’s the percentage of revenue retained from your existing customers over a given period of time. As the primary owners of customer retention and expansion opportunities, NRR is particularly important to CS teams because it helps signal the product’s ability to continually meet the needs of customers and grow its reach while minimizing churn.

リテンションとNRRデータに対して行動を起こす方法

• Retention:
  In general, the fewer features a user interacts with on a regular basis, the less likely they are to glean value from your product. A steady decline in feature retention could be an early indicator of churn. Segment your retention data (e.g. by role, company size, or free users vs. paying customers) to compare feature retention across different subsets of users and determine how their behaviors differ.
• NRR:
  Examine the accounts who contributed the greatest dips or increases in NRR. Dig into the behaviors of those users to identify what they did well (contributing to increased NRR) or where they were struggling (contributing to decreased NRR). This can help you replicate positive workflows or onboarding processes from your customers who expanded; or get ahead of product issues, gaps in enablement, or other factors that contributed to a negative experience for your customers who churned.

7. ネットプロモータースコア（NPS）

Net Promoter Score (NPS) is one of the most common ways companies gauge customer loyalty. It is delivered via a single question that asks, “How likely are you to recommend this brand to a friend or colleague?”, with customers answering on a 0-10 scale. Customers who answer 9 or 10 are your “Promoters,” those who answer 7 or 8 are “Passives,” and those who answer 0 through 6 are “Detractors.” 

NPSは非常に浸透しているため、同業他社に対する組織のベンチマークとして有効な手段です。また、一定の時間単位で収集し、追跡しやすい指標でもあります。CSチームは、日々顧客と接しており、それぞれのスコアの背後にある定性的な状況を把握することができるユニークな立場にあるため、顧客のNPSスコアを調査し、対応するのに最適な能力を備えています。NPSは、全体的な拡大や成功のシグナルとしても有効です。顧客のブランド支持率は、顧客の幸福度、ひいてはビジネスの成長を示す代用指標となります。

NPSデータに対して行動を起こす方法

• アカウントレベルと個人ユーザーレベルでNPSを測定します。アカウントレベルのスコアは、各顧客の平均的なセンチメントを理解するのに役立ちます。一方、ユーザースコアは、スコアを上下させる主要なペルソナがいるかどうかを明らかにするのに役立ちます（そして、その行動をさらに調査し、必要に応じて再現したり介入したりすることができます）。
• 回答者には、常に数値スコアのほかにコメントも記入してもらいます。このような定性的な情報は、貴重な背景知識を与えてくれるほか、必要に応じて顧客をフォローする際の自然なきっかけになります。

8. フィードバックと機能リクエスト

Customerfeedback is information provided by customers about their experience with a product or service. Its purpose is to reveal their level of satisfaction and help product, customer success, and marketing teams understand where there might be room for improvement. Feature requests are a subset of customer feedback—specifically related to the features or optimizations customers and users want to see from the product in the future. CS teams are in an optimal position to hear both feedback and feature requests first-hand from customers, and help other teams across the organization—like product and engineering—gather these insights in a single place to be triaged and considered for the roadmap. 

プロダクトチームがすべての機能リクエストに対応することは不可能（かつ好ましくない）ので、顧客やユーザーから最もリクエストの多い機能を把握することは非常に有効です。この情報はCSMにもメリットがあります。大口の顧客の解約を防ぐには、アカウントごとに上位のリクエストを分析して、投資に値する改善点があるかどうかを確認することが重要です。また、CSMは顧客とのミーティングの際に、これらの要望を積極的に持ち込んで、より詳しい状況を把握したり、特定の機能が将来のリリースで検討されている（あるいはされていない）理由を説明したりすることができます。

フィードバックと機能リクエストデータに対して行動を起こす方法

• Feedback:
  Use product analytics to correlate how customers are using the product with their feedback to get a complete picture of their journey. For example, if a customer provides feedback that they think a particular workflow feels overly complicated, you can look into their analytics data to see the path they typically take to complete the workflow, as well as which features they engage with along the way. This could help you uncover whether a change to the product’s functionality or UI might be needed, or whether the issue actually stems from an enablement gap that could be solved with an in-app guide.
• Feature requests:
  Take a look at requests made at the account level before each QBR with your customers. This will help you feel prepared to answer their questions and gives you the opportunity to proactively get more context about the challenges they’re hoping to solve. And ultimately, it also builds trust and helps your customers feel heard and valued.

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