Rebiz Results
“That Which Gets Measured, Gets Improved”
What matters and what works – straight from the ReBiz Data science Team
As a retailer, better data helps answer important questions like:
- Why are we up or down, is it us or the market?
- Why do these stores routinely underperform the others?
- Why do we see swings in conversion from day to day?
- The numbers changed, is it traffic or performance or something else?
- Specifically, what should we expect of traffic by day and hour next week?
On average ReBiz users simplify their management process, focus on what matters the most, coach with accurate data in hand and see returns of more than ten times what they pay for our monitoring services (yes, we measure that too!).
90 Day Conversion Rate Study
A comprehensive study was carried out on 600 retail stores that implemented customer-only traffic count verification and employee-level sales conversion tracking. These stores were observed over a 90-day period. The stores’ performance over their first 30 days (unaffected) was compared to their performance over days 31 through 90 (affected)
Traffic Was Stable: Overall monthly traffic showed only minor fluctuations, with days 31-90 reporting a slight decrease of approximately 2.95% compared to the first 30 days.
The Results
Baseline
Overall monthly traffic showed only minor fluctuations
Impact of Manager Presence on Sales Conversions
This is one of the most frequent questions we get, it is actually two questions:
- How much time should managers be onsite?
- How much does it impact results?
The ReBiz data team analyzed this over 2,000+ stores. We used a couple of long-known standards for manager in-store presence.
The Results:
MANAGER IN-STORE HOURS & RETAIL SALES
Store manager
District manager
No. of hours in store per week
Average Conversion Rate
No. of hours in store per week
Average Conversion Rate
- More than 40 hours
- Less than 30 hours
- Delta
- 20.50%
- 16.30%
- 3.8 points (25.7% difference)
- More than 30 hours
- Less than 30 hours
- Delta
- 20.64%
- 18.84%
- 1.8 points (9.5% difference)
Store manager
No. of hours in store per week
Average Conversion Rate
- More than 40 hours
- Less than 30 hours
- Delta
- 20.50%
- 16.30%
- 3.8 points (25.7% difference)
District manager
No. of hours in store per week
Average Conversion Rate
- More than 30 hours
- Less than 30 hours
- Delta
- 20.64%
- 18.84%
- 1.8 points (9.5% difference)
The specific thresholds for manager in-store time vary by retailer. We often work with clients to look at their trends on both sides; how many hours is not enough and above how many hours do we stop seeing positive returns. To begin this work, we simply activate our monitoring services and start collecting and reviewing data.
The Impact of Management Styleon Results
“Clean Data Lifts Performance, No Matter the Management Style”
Our clients have many different management styles. Some are data-driven, active managers who lean into employee-level metrics and cycles of coaching and performance improvement. Others take more of a team-based approach. Others underemphasize conversion so as to focus on customer experience. Some just want to know when employees aren’t doing their jobs before it infects everyone else.
- Individual management requires individual data
- Active management relies on deeper insights
- All boats rise with accountability
Here’s what we find. Regardless of the interaction style between managers and in-store employees, having verified data and simply knowing the truth has a consistent, positive effect on performance.
Knowing the basic performance metrics for each employee, store and district actually simplifies management and reduces the number of conversations. Instead of going into a coaching session needing to probe for issues, leaders already know what’s working and what’s not. Conversations are more relevant, shorter, and more meaningful to the employee. Just as important, employees get “accused” of the wrong things less often.
In reality, simply knowing that someone cares and knows the difference stops much of the slacking off.
- Which management style do you use?
- Curious what the data says you should track and how to use it?