Human Assisted Onboarding: Key Performance Indicators

Retention

8%

Revenue

8%

Email Campaigns

8%

LTV

8%

Onboarding Completion

16%

Churn

16%

CS Feedback

17%

Expansion

25%

Team Activation

25%

Usage

25%

Initial Value

42%

Activation

42%

NPS

50%

Data Analysis

Top KPIs

Top KPIs are NPS (50%), Activation (42%) ,Time to Initial Value (42%), Key Feature Adoption (33%), Usage (25%) and Team Activation (25%).

Product Measurements

Product measurements are critical, despite the limited involvement of Product Management (38%)*, due to the continuous monitoring of the customer journey from Customer Success.

Key Takeaways

Customer Advocacy

Customer advocacy (NPS) should consider additional usage metrics. In the opposite scenario acts as a lagging indicator and does not deliver objective measurements

Retention

Product engagement performance indicators are intrinsically related to Retention on Self Serve onboarding, but on Human Assisted, additional parameters are considered.

Being subject to Customer Success activations, Retention substitutes a KPI for 8% while Usage and Key Feature Adoption (Depth of Use) have a 33% and 25% of preference respectively.

Breadth of Use

Activation indicates how successfully users embark into products’ value and should be measured via the lens of team activation (Breadth of use). While most participants attested to getting internal buy-in from end users as the number one challenge, Team Activation is considered important only by 25%.

Expansion

While Retention is neglected, its offspring, Expansion, is measured by 25%. Expansion is also subject to CS practices. Qualitative data reaffirm that consistency in meeting buyers needs, via one on one interactions, is the number one criterion leading to accounts’ long term prosperity.

High Touch vs. High Tech

Despite the need to provide exceptional customer experience based on personal engagement, harmonization among the high touch techniques and high-tech techniques is essential.

Targeted in application training is not supposed to be used to replace one on one interactions. When used in conjunction with product data, it supplements Customer Success activations and allows CSMs to focus more on customers’ needs.

In addition, harmonization among practices reduces onboarding costs and increases adoption rates.

High Touch vs. High Tech Use Cases

Use Case: Pendo

Pendo, the popular product experience software, is a living proof that this balance can be achieved. When new customers are onboarded, Customer Success sets up one-on-one calls and leverages the software’s features to train users at the same time.

Being ingrained into product data analysis as an organization, the provided training at scale always considers the POE metrics to provide context behind users’ usage. Those practices provide positive outcomes for Customer Success since its constituents have the luxury to focus on business objectives by dedicating only 25-30% airtime in application onboarding.

Use Case: Userlane

Userlane, the popular onboarding S/W, serving mostly enterprise customers launched a while ago an alternate asynchronous onboarding in addition to its Human Assisted strategy. The vendor uses the S/W own features to self serve end users all the way through without compromising the required decision making between the two parties.

The “Inception project” as it’s known internally improved the delivery of the onboarding process and increased adoption (+48%). The implementation of targeted walkthroughs within the product allowed a thorough personalized, albeit automatic onboarding process that didn’t require the active participation of different units. Additionally, time to initial value was decreased and after launch, buyers could go through the set up autonomously.

Human Assisted Onboarding: A/B Constituents

The optimization of product engagement practices is a rather big discussion, but mostly an outcome of extensive experimentation. Οn Self-serve onboarding, where product engagement prevails, experimentation is perceived as a given. On the flip side, when targeting Mid Market and Enterprise customers, customization is subsequent to any onboarding practice. The secret, in both cases, is disposing scalable practices cautiously by focussing on the context behind usage, always in conjunction with historical data analysis.

Email Campaigns are the number one A/B constituent with 25% preference.

Marketing Content is iterated by a 16%. At the same time, an equal 16% does not experiment on any aspect of the onboarding strategy.

Role-Based onboarding, Activation, UI/UX, Product Content optimization, Hotspots, and Sales Outreach have 8% preference.

Human Assisted Onboarding: Scalable Tactics

In App Demos

6%

In App Surveys

20%

Hotspots

20%

Progress Bars

20%

In App Tutorials

33%

Welcome Messages

46%

CRM Flows

46%

Tooltips

53%

Live Chat Flows

53%

Walkthroughs

60%

NPS

66%

Email Campaigns

73%

Data Analysis

Key Tactics

  1. Email Marketing Campaigns, NPS, and Walkthroughs are top of mind with 73%, 66%, and 60% preference respectively.
  2. Product tours, Live Chat Flows, and Tooltips are preferred from half (53%) of the participants.

Less Preferred Tactics

Customer feedback (In-App Surveys 20%) and in-app training (In Product Tutorials 33%) are not among the top preferred tactics.

Key Takeaways

Role-Based Onboarding

If we compare the A/B constituents versus the automation tactics, we realize that onboarding owners have multiple in-app engagement practices at hand. Limited investment on Role Based Onboarding (8%) indicates that in-app practices suggest a predispose route and don’t consider the context behind usage.

Breadth

Organizations in need to onboard hundreds of end users should optimize product experience by focusing on POEs metrics (e.g. Breadth) performance. In the opposite scenario, Sales and Customer Success will act as product champions who miss context behind users’ behavior.

Next: Self-Serve Onboarding

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