Interview with Sarah Kim, Head of HR Analytics at Evergreen Wealth Management
Q1: Sarah, from your experience, what’s the biggest misconception HR teams at mid-market insurance firms have about multivariate testing when trying to measure ROI?
A1: The biggest mistake I see is confusing multivariate testing with A/B testing — they’re related but serve different purposes. Multivariate testing simultaneously tests multiple variables and their combinations, which can reveal interaction effects. However, this complexity often leads to underpowered tests if sample sizes aren't big enough.
For example, a 2023 McKinsey report highlighted that 60% of mid-market insurance firms ran tests without adjusting for sample size, resulting in inconclusive results. If you’re testing four variables each with two variants, you have 2^4=16 combinations. For a company with 200 employees, that’s often not enough data to detect meaningful differences in turnover or engagement with statistical confidence.
Bottom line: Test fewer variables or longer, or risk wasting time and resources on noisy data.
Multivariate vs. A/B Testing: What HR Professionals Need to Know
1. Complexity vs. Clarity: Picking the Right Approach
| Factor | Multivariate Testing | A/B Testing |
|---|---|---|
| Number of variables | Multiple at once (e.g., communication style + timing) | One variable at a time (e.g., email subject) |
| Sample size requirement | Very high — grows exponentially with variables | Lower — easier for smaller employee bases |
| Insights gained | Interaction effects between variables | Direct effect of single change |
| Typical HR use cases | Complex communications, policy bundles | Single-variable messaging (e.g., benefits email) |
For mid-market wealth-management insurance firms, where HR teams often have limited headcount and data volume, A/B testing is often more practical unless the test runs several months.
Q2: How have you seen HR teams prove ROI through multivariate testing?
A2: One example stands out. An HR team at a mid-market insurance firm in Chicago wanted to improve uptake of their new retirement savings plan. They tested three email elements:
- Subject line (benefit-focused vs. deadline-focused)
- Send time (morning vs. afternoon)
- Email length (short vs. detailed)
By running a multivariate test over 6 weeks with 300 employees, they found that “deadline-focused” subject lines combined with afternoon sends and short emails increased click-through rates by 72%. That translated into a 9% increase in plan enrollment compared to the previous quarter.
They tracked ROI by comparing enrollment increases to the cost of their HR platform and found a 5:1 return after 3 months. This quantitative proof made it easier to get budget for ongoing testing and employee engagement tools.
Why dashboards and reporting are critical for ROI measurement
Without clear dashboards, multivariate testing results can get lost in spreadsheets. HR teams should build or use dashboards that:
- Show lift percentages in engagement, retention, or enrollment
- Track costs vs. gains over time
- Segment results by employee demographics (e.g., tenure, department)
For example, using tools like Tableau or Power BI integrated with survey platforms such as Zigpoll, Qualtrics, or Medallia can streamline reporting to senior management.
Q3: What are common pitfalls HR teams fall into when measuring ROI from these tests?
A3: Three frequent mistakes:
- Ignoring external factors — Economic shifts, regulatory changes, or company announcements can skew results. For example, a sudden change in 401(k) matching policy might spike enrollments unrelated to email variations.
- Overlooking statistical significance — Teams sometimes declare winners with a 10% lift but no statistical confidence, leading to false positives.
- Not aligning metrics with business impact — For instance, measuring open rates without connecting them to downstream actions like benefit enrollment or retention improvements.
The downside? Misguided decisions and wasted budgets.
Advanced tactics for mid-market HR teams in insurance
2. Prioritize Variables by Impact and Feasibility
Focus on the top 2-3 drivers of employee behavior. For instance, communication cadence and message framing often have bigger ROI than color schemes or email signatures.
3. Use Sequential Testing to Manage Sample Size
Instead of testing all variables at once, run sequential A/B tests informed by initial results. This can reduce sample size needs from thousands to hundreds while still uncovering insights.
4. Incorporate Qualitative Feedback
Combine tests with quick employee pulse surveys using tools like Zigpoll or SurveyMonkey. Qualitative data illuminates why a variation works, not just that it does.
Q4: Which specific KPIs should mid-market HR teams track to prove ROI in wealth-management insurance?
A4: Focus on metrics tied directly to business outcomes. For example:
- Benefit plan enrollment % change (e.g., increase from 45% to 52%)
- Employee retention rate changes (e.g., reducing voluntary turnover by 3%)
- Engagement scores from pulse surveys (ideally improving by 5-7 points on a 100-point scale)
- Cost per hire reduction if testing recruitment messaging
A 2024 Deloitte HR Benchmark survey found insurance firms that linked testing to these KPIs reported 20% higher stakeholder satisfaction with HR initiatives.
How to build and share ROI dashboards for stakeholder buy-in
5. Standardize Reporting Cadence
Monthly updates with clear visuals and narratives help keep leadership engaged.
6. Segment by employee groups
Show how campaigns affect key cohorts — e.g., producers vs. back-office staff — because ROI drivers differ.
7. Highlight dollar impact not just percentages
Translate improvements into savings or additional revenue. For instance, “Reducing turnover by 2% saves $150K annually in replacement costs.”
Q5: Any last advice for HR pros running multivariate tests on limited budgets and resources?
A5: Yes. Focus on these three:
- Start small, measure rigorously — Running a quick A/B test on a key email can yield faster ROI proof than sprawling multivariate tests.
- Leverage existing platforms — Many HRIS systems have basic A/B testing and reporting tools baked in.
- Partner with analytics teams — Getting help with statistical testing and dashboard setup ensures you don’t misinterpret data.
Remember, testing won’t work if you chase vanity metrics. Tie every experiment back to clear financial impact or talent KPIs.
Summary of Tested Strategies and Expected ROI Impact
| Strategy | Typical ROI Lift (Insurance Example) | Caveat |
|---|---|---|
| Multivariate email tests | 6-9% increase in benefit enrollment | Requires large samples |
| Sequential A/B testing | ~4-6% improvement in engagement/pulse scores | Takes longer to complete tests |
| Qualitative + quantitative | Deeper insights, leading to >10% turnover reduction | Needs survey tools and buy-in |
| Dashboard reporting | 20% higher stakeholder satisfaction | Time investment to build |
Multivariate testing in mid-market insurance HR is a powerful tool when wielded carefully. Run tests with realistic sample sizes, focus on business-critical metrics, and communicate results clearly to build ongoing support and demonstrate real ROI.
