Best Practices

Top 14 Triggers and Alerts for Customer Success Teams

Akshaye Badiger

November 14, 2023

10 min read

Critical Triggers For pre-empting customer issues

A Proactive Approach to Customer Satisfaction

Do you ever feel like your customer success team is stuck reacting to issues instead of building long-term relationships? In the longer run, firefighting churn can take up all your days while strategic growth opportunities can go untapped.

There is a better way. Most customer success teams today use data-driven alerts to get ahead of problems and delight users. Identifying issues early allows you to retain and engage customers when it matters most.

This article will explore the 14 most critical alerts for customer success teams. You'll discover:

  • How alerts enable proactive, not reactive, success strategies.
  • How alerts can strengthen loyalty across the customer lifecycle.
  • Real examples of alerts driven by customer health metrics.
  • Tools that simplify managing alerts at scale.
  • Tips to build an alert framework that transforms random noise into actionable signals.

The future of customer success is proactive, personalized, and powered by contextual alerts. Read on to learn how leading teams make that future a reality and turn subscribers into delighted customers.

The Role of Alerts in Proactive Success

A humorous cartoon by shep hyken on customer success
Source: Shep Hyken

Alerts act like an early detection system, flagging changes in customer behavior or metrics that signal potential issues or opportunities.

By monitoring and acting on these real-time signals, customer success teams can identify problems at their earliest stages before they escalate or negatively impact the customer experience.

Benefits of a proactive approach

  • Increased retention and reduced churn by addressing problems swiftly
  • Higher lifetime value by delighting customers with contextual service
  • Improved loyalty through ongoing, personalized interactions
  • Modern teams leverage alerts as a key component of their proactive customer management strategies. Alerts allow them to detect emerging signals and engage users with relevant, timely outreach - transforming reactive firefighting into satisfying, loyal relationships.

Key Triggers for Customer Success Teams

To keep customers engaged, we need to watch for key triggers that signal their experience might be slipping. SQL queries help us find these triggers by looking at data in your warehouse (Postgres, MongoDB, Snowflake, etc) or Google Sheets or SaaS platforms like HubSpot, Salesforce, Intercom, Zendesk, etc.

Data Readiness Check: For setting up these triggers, we're assuming your data is organized into a schema with:

  • Users: Profiles including customer attributes and metadata.
  • Interactions: Records of how customers interact with your product.
  • Transactions: Details of customer purchases, subscriptions, and payments.
  • Support: Logs of customer support tickets and resolutions.

If your schema is different, you'll need to adjust the queries. It's wise to seek help from your data teams if you're not comfortable making these changes yourself.

With our data set up, let's move on to identifying the triggers that can help us act fast and keep our customers happy.

Alerts on Critical Triggers for Customer Retention

Let's dive into 14 critical triggers that every customer success team should watch out for:

1. Sudden Drop in Engagement Alerts

Alert Title: Engagement Drop-off Alert

Trigger: A notable decrease in user activity within the application.

Data Source: User activity tracking system (e.g., Google Analytics, Mixpanel).

Ideal Followup Action: Investigate the cause of reduced engagement and reach out to the user with targeted surveys, product tips, or special offers to re-engage them.

Example: Suppose you want to monitor the number of sessions a user has had in the last 30 days to the number in the previous 30 days, alerting if there’s a 50% drop.

Here’s a sample SQL query for this:


SELECT user_id,
       COUNT(DISTINCT session_id) AS sessions_last_30_days,
       COUNT(DISTINCT session_id) AS sessions_previous_30_days
FROM user_activity
WHERE activity_date BETWEEN CURRENT_DATE - INTERVAL '60 days' AND CURRENT_DATE
GROUP BY user_id
HAVING sessions_last_30_days < 0.5 * sessions_previous_30_days;


2. Incomplete Onboarding Alerts

Alert Title: Incomplete Onboarding Alert

Trigger: The user has not completed essential onboarding steps.

Data Source: Onboarding tracking system within the app (e.g., Pendo, Appcues).

Ideal Followup Action: Send a personalized email or in-app message with a guided walkthrough offer. Create a support ticket in Zendesk for the customer success team to follow up.

Example: Say you want to identify users who signed up in the last week but haven't completed their profiles or walkthroughs.

Here’s a sample SQL query for this:


SELECT user_id,
       completed_profile,
       completed_walkthrough
FROM user_onboarding
WHERE signup_date BETWEEN CURRENT_DATE - INTERVAL '7 days' AND CURRENT_DATE
AND (completed_profile IS FALSE OR completed_walkthrough IS FALSE);

3. Missed Key Actions Alerts

Alert Title: Key Milestone Missed Alert

Trigger: The user has not performed expected actions within a set timeframe.

Data Source: User interaction logs (e.g., internal event tracking systems).

Ideal Followup Action: Trigger an in-app notification or email reminding the user of the benefits of these actions. Post a message to a specific #customer-engagement Slack channel to notify the team.

Example: You want to find users who have not performed key actions in the past 15 days.

Here’s a sample SQL query for this:


SELECT user_id,
       DATEDIFF(CURRENT_DATE, last_action_date) AS days_since_last_action,
       key_actions_completed
FROM user_actions
WHERE last_action_date < CURRENT_DATE - INTERVAL '15 days'
AND key_actions_completed < expected_actions;

4. Post-Purchase Inactivity Alerts

Alert Title: Post-Transaction Inactivity Alert

Trigger: No user activity following a purchase, upgrade, or renewal.

Data Source: Transaction and user activity systems (e.g., internal sales database, CRM like Salesforce).

Ideal Followup Action: Send a targeted email with resources to get started or offer a one-on-one product usage consultation. Alert the account manager through a CRM task for a follow-up.

Example: You want to spot users who haven't been active since their last purchase.

Here’s a sample SQL query for this:


SELECT u.user_id,
       t.transaction_id,
       MAX(a.last_activity_date) AS last_activity
FROM users u
JOIN transactions t ON u.user_id = t.user_id
LEFT JOIN activity a ON u.user_id = a.user_id
WHERE t.purchase_date > a.last_activity_date
AND t.purchase_date < CURRENT_DATE - INTERVAL '7 days';


5. Plan Downgrade Alerts

Alert Title: Service Plan Downgrade Alert

Trigger: The user switches to a lower-tier service plan.

Data Source: Subscription management system (e.g., Stripe, Zuora).

Ideal Followup Action: Send an automated email to understand their decision and offer tailored incentives. Create a high-priority ticket in the CRM for the account manager to offer personalized solutions.

Example: You want to detect users who have downgraded their plans in the last month.

Here’s a sample SQL query for this:


SELECT customer_id, old_plan, new_plan
FROM plan_changes
WHERE new_plan_value < old_plan_value
AND change_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE;

6. Failed Transaction Alerts

Trigger: The user experiences a failed transaction attempt.

Data Source: Payment processing system (e.g., Stripe, PayPal).

Ideal Followup Action: Send an empathetic email offering assistance with the payment process or exploring alternative payment options. Post an alert to the #billing Slack channel to review the incident.

Example: You want to find users with multiple failed payment attempts in the last month.

Here’s a sample SQL query for this:


SELECT user_id,
       COUNT(failed_transaction_id) AS failed_attempts,
       MAX(failure_date) AS last_failure_date
FROM failed_transactions
WHERE failure_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
GROUP BY user_id
HAVING failed_attempts > 1;

7. Increased Support Contacts Alerts

Alert Title: High Support Activity Alert

Trigger: A rise in the number of support tickets or calls from a user.

Data Source: Customer support platforms (e.g., Zendesk, ServiceNow).

Ideal Followup Action: Assign a customer success agent to personally address any issues and ensure resolution. Automate Zendesk ticket creation for high-touch follow-up.

Example: You want to track users who have opened multiple support tickets in the past month.

Here’s a sample SQL query for this:


SELECT user_id,
       COUNT(ticket_id) AS number_of_tickets
FROM support_tickets
WHERE creation_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
GROUP BY user_id
HAVING number_of_tickets > 3;

8. Negative Sentiment Alerts

Alert Title: Customer Dissatisfaction Alert

Trigger: Negative feedback such as poor app store reviews or low CSAT scores.

Data Source: Feedback platforms and CSAT score aggregators (e.g., Trustpilot, SurveyMonkey).

Ideal Followup Action: Prompt customer success to reach out with personalized recovery offers and feedback requests. Trigger a real-time alert in the customer success team's Slack channel.

Example: You want to identify users with an average CSAT score lower than 3 in the last month.

Here’s a sample SQL query for this:


SELECT user_id,
       AVG(csat_score) AS average_csat
FROM customer_satisfaction
WHERE survey_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
GROUP BY user_id
HAVING average_csat < 3;


9. Competitor Engagement Alerts

Alert Title: Competitor Interaction Alert

Trigger: Customer mentions or shows interest in a competitor.

Data Source: Social listening tools, search analytics (e.g., Mention, Google Analytics).

Ideal Followup Action: Engage the customer with a comparison of value offerings or loyalty incentives. Alert the marketing team via a Slack notification for targeted retention campaigns.

Example: You want to find users who have mentioned competitors in the last month.

Here’s a sample SQL query for this:


SELECT user_id,
       SUM(competitor_mentions) AS total_mentions
FROM competitor_engagement
WHERE engagement_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
GROUP BY user_id
HAVING total_mentions > 0;

10. Third-Party Data Churn Alert

Alert Title: External Risk Indicator AlertTrigger: Third-party data predicts potential churn.Data Source: External data providers, and market intelligence services (e.g., Experian, Dun & Bradstreet).Ideal Followup Action: Initiate a strategic account review and personalized outreach to preempt churn. Automate an internal alert for the customer success team to take immediate action.

Example: You want to assess current churn risk scores provided by third-party data services.

Here’s a sample SQL query for this:


SELECT user_id,
       churn_risk_score
FROM third_party_risk_assessment
WHERE assessment_date = CURRENT_DATE;

11. Outreach Non-Engagement Alert

Alert Title: Outreach Ignored Alert

Trigger: Customer does not engage with emails or in-app messages.

Data Source: Email and communication platforms (e.g., Mailchimp, Intercom).

Ideal Followup Action: Test alternative communication strategies and messages. Set a task for the customer success team in the CRM to attempt a different engagement method.

Example: You want to identify users who have not opened any of the several emails sent in the past month.

Here’s a sample SQL query for this:


SELECT user_id,
       SUM(emails_sent) AS emails_sent,
       SUM(emails_opened) AS emails_opened
FROM email_communications
WHERE send_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
GROUP BY user_id
HAVING emails_opened = 0 AND emails_sent > 3;

12. Leaderboard Decline Alerts

Alert Title: Activity Ranking Drop Alert

Trigger: User drops in leaderboard rankings or activity levels.

Data Source: Platform activity logs (e.g., for gaming, social, or SaaS products with user rankings).

Ideal Followup Action: Offer incentives or highlight new features to re-engage. Post a strategic alert in the product team’s Slack channel to consider user experience improvements.

Example: You want to spot users who have dropped more than five places in the leaderboard since the last ranking period.

Here’s a sample SQL query for this:


SELECT user_id,
       previous_rank,
       current_rank
FROM user_rankings
WHERE ranking_date = CURRENT_DATE
AND previous_rank > current_rank + 5;

13. Unengaged Cohorts Alerts

Alert Title: Cohort Engagement Drop Alert

Trigger: Specific user cohorts showing a higher rate of disengagement or churn.

Data Source: Analytics platforms with cohort analysis features (e.g., Amplitude, Google Analytics).

Ideal Followup Action: Launch targeted re-engagement campaigns and analyze cohort data for product improvement insights. Create a task in the CRM for the marketing team to initiate the campaign.

Example: You want to identify cohorts with an engagement rate lower than 20%.

Here’s a sample SQL query for this:


SELECT cohort,
       COUNT(user_id) AS total_users,
       AVG(daily_active_users) / AVG(total_users) AS engagement_rate
FROM user_cohorts
GROUP BY cohort
HAVING engagement_rate < 0.2;

14. Churn Survey Feedback Alerts

Alert Title: Churn Survey Insight AlertTrigger: Receipt of negative feedback in churn surveys.

Data Source: Survey platforms (e.g., Typeform, SurveyMonkey).

Ideal Followup Action: Conduct a thorough review of feedback and implement changes where needed. Notify the product and customer success teams to take corrective action.

Example: You want to spot users who have given a score of 6 or below in recent churn surveys.

Here’s a sample SQL query for this:


SELECT user_id,
       survey_score,
       feedback
FROM churn_surveys
WHERE survey_date BETWEEN CURRENT_DATE - INTERVAL '30 days' AND CURRENT_DATE
AND survey_score <= 6;


Leveraging Alerts for Strategic Customer Success

Effective alert systems are a game-changer for customer success teams. They enable a shift from merely reacting to issues to nurturing long-lasting customer relationships. Here’s how teams can use alerts strategically:

  • Adoption Monitoring: Implement alerts to track how customers use your product. If usage dips or if customers skip key features, it’s a chance to offer proactive education, ensuring they fully leverage your product’s value.
  • Renewal Tracking: Set up alerts for upcoming renewals. Reach out ahead of time to ensure customers have everything they need for a smooth renewal process, addressing any concerns that might prevent it.
  • Milestone Anticipation: Use alerts to celebrate customer milestones. Whether it's their 100th login or a year since they joined, recognising these moments can deepen customer engagement.
  • Creation a delightful Customer Experience: Design alerts to find moments to go above and beyond for your customers. This could be a surprise upgrade or a congratulatory message for a customer achievement.

By proactively engaging with your customers at critical moments identified by intelligent alerts, customer success teams can build trust and loyalty that lasts the entire lifecycle of the relationship.

Best Practices for Setting Up Customer Success Alerts You Need to Adopt Now

With a few simple practices in place, you ensure your alerts work for you and your customers, making sure that every issue is an opportunity to learn more about your users.

1. Set Clear Thresholds

Define exact conditions for alerts to avoid ambiguity.

Example: Set an alert when the number of weekly active users drops below 80% of the monthly average, indicating a potential engagement issue.

2. Deliver Actionable Details

Ensure alerts provide sufficient information for immediate action.

Example: An alert for decreased usage should include the user's activity history and product usage patterns to inform the outreach strategy.

3. Use Proper Monitoring Frequency

Adjust the monitoring frequency based on the metric's impact on customer experience.

Example: Daily checks for critical feature engagement, but monthly for general newsletter interaction trends.

Graphic showing an alert notification on decreased user activity
A sample alert showing a drop in a metric

4. Minimize False Positives

Calibrate alerts to ignore normal fluctuations and only flag significant anomalies.

Example: Only trigger a high churn risk alert if a customer's product usage drops consistently for three weeks in a row.

5. Log Alerts for Accountability

Maintain a log to track alerts and follow-ups, ensuring issues are addressed.

Example: Use a CRM to log when and how each alert was resolved, building a reference for future similar scenarios.

6. Refine Continuously

Regularly review and adjust alert parameters to ensure they remain relevant.

Example: If certain alerts never result in actionable follow-ups, either recalibrate their thresholds or discontinue them.

7. Automate When Possible

Where appropriate, use automation to handle routine alert responses.

Example: Automate re-engagement emails when a user hasn't logged in for 10 days.

8. Pick User-Centric Channels

Choose the most effective communication channel based on the user’s preferences and the urgency of the alert.

Example: For critical account issues, send alerts via phone call or SMS; for less urgent matters, opt for email.

9. Categorize by Priority

Clearly mark alerts by their level of urgency so that teams can prioritize their responses.

Example: Tag alerts related to system downtime as 'urgent' and slower-than-usual response times in customer service as 'low'.

10. Adopt Escalation Protocols

Define clear escalation paths for alerts that are not resolved within a certain timeframe.

Example: If a critical alert is not addressed within one hour, it escalates to the senior management team.

Graphic showing an alert notification warning critical system downtime
A sample alert showing an escalation

11. Utilize Playbooks

Have detailed action plans (playbooks) for different types of alerts to standardize responses.

Example: For a high churn risk alert, follow a playbook that includes reaching out with a customer satisfaction survey followed by a personalized offer.

With these practices, each alert is crafted to be clear, timely, and relevant, enabling teams to act swiftly and effectively.

Managing your Customer Success Alerts with Locale

What happens next once an alert gets triggered is crucial. A central incident response system like Locale acts as a control tower, providing

  • A centralized platform to oversee and coordinate churn response workflows.
  • Tools to easily build conditional, multi-step workflows and playbooks.
  • Integration of alert context to inform follow-up actions, ensuring they are as relevant and personalized as possible.
  • the ability to track the entire lifecycle of an alert from trigger to resolution, offering transparency and accountability.
  • Centralize your retention campaigns and responses, providing a single source of truth for your strategies.
Illustation depicting how quickly users can connect their data source to quickly setup alerts on Locale's platform

Without such a system, teams might find themselves in disarray. Here’s what happens if you don’t use a centralized control tower to manage and act on customer success alerts:

  • Alerts get lost outside of regular workflows.
  • There is no single source of truth driving systematic responses.
  • Efforts can be duplicated, or worse, critical alerts can be missed altogether.

Conclusion

A well-thought out alerting and monitoring framework is the starting point for proactive customer retention. However, without a robust system like Locale, these alerts can't reach their full potential. Locale offers the tools to not only alert but also to act, ensuring that each alert is an opportunity to strengthen customer relationships.

With playbooks and automated resolutions, Locale turns alerting into a strategic asset for your customer success team.

Ready to see Locale in action? Reach out to a retention specialist and start transforming your customer success strategy today.

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