13. Ad Image 1
Ad Call To Action 1
Non connected images &
copies on landing page
Using image 1 and call to
action 1 on landing page
Reg CVR 7%
Reg CVR 11%
14. First Name
Last Name
Email
Password
Phone Number
Company Name
Company Size
7% Overall form CVR to reg
First Name
Last Name
Email
Password
15% Overall form CVR to reg
Company Size
Company Name
Phone Number
First Stage Second Stage
Industry
Industry
New form also enabled reengagement with emails signups
who did not complete registration
15.
16. 0
5
10
15
20
25
30
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day
10
Day
11
Day
12
Day
13
Day
14
Day
15
Day
16
Day
17
Day
18
Day
19
Day
20
UniqueSales
Days after registration
Amount of unique sales / Days after initial registration
Sales after
day 13 flat
lined
Drop in
sales after
Day 3
17. 0
5
10
15
20
25
30
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day
10
Day
11
Day
12
Day
13
Day
14
Day
15
Day
16
Day
17
Day
18
Day
19
Day
20
UniqueSales
Days after registration
Discount
offering
25% off
Discount
offering
50% off
18.
19. 0
50
100
150
200
250
300
0.0%
0.1%
0.1%
0.2%
0.2%
0.3%
0.3%
0.4%
0.4%
0.5%
Month 1 Month 2 Month 3 Month 4 Month 5
AverageSalesPrice(USD)
ConversionRateToTransaction
ASP vs Monthly CVR
Conversion Rate To Transaction Average Sales Price
$-
$2.00
$4.00
$6.00
$8.00
$10.00
$12.00
$14.00
$16.00
Month 1 Month 2 Month 3 Month 4 Month 5
(USD)
Revenue / New user
Revenue / New user
Editor's Notes
My name is Elad and I’m really excited being here.
Luke, thank you for a wonderful presentation
I’m really excited to meet you all today and sharing a real case study telling the story of an exciting SaaS platform.
Few words about myself, I’m the CEO of PandaPepper, digital marketing & analytics shop, prior to that I headed the marketing & BI in Fiverr, prior to that I was working for Matomy & Maersk – a danish conglomerate.
We work with all sort of businesses to help them reaching their business objective.
Before getting started, I’d like to spend a minutes and align definitions.
A great way to describe what optimization actually is, is by using the Kaizen Cycle.
Was born with Japanese assembly lines
Acknowledge the fact that improvement is iterative process and not linear.
Reflect the assent of optimization - gain a baseline first, measure later.
So just to sum-up what we so far had,
Iterative process, which is ongoing and requires long term commitment.
Requires scientific mindset, but as we are out of the academy we can allow judgment calls.
Data driven, which requires the right skill set and tools.
Hyper measurable, hence easy to demonstrate success. Nevertheless, the challenge is not what to measure but what not to measure.
Requires agility: mindset, coding, product, design.
THE CUSTOMER:
B2B SaaS platform enabling SMBs to sell more
THE CHALLENGE:
Advertising spend was resulting in a negative ROI
HOW DID WE MEASURE SUCCESS?
Revenue per new user
WHAT DID WE DO TO DELIVER SUCCESS?
1. Optimize advertising
2. Optimized product
3. Optimized Reengament
When speaking about analytics, it’s important to understand it’s functionality make sure this functionality is met in the minimal effort possible.
The functionality is:
Measuring business performance
Understand how people are engaging with your product.
Google Analytics is an amazing platform that keeps getting better. Under any circumstances, I wouldn’t give it up.
You always have to test different audiences, it’s clear.
But why? In order to draw this.
Only once did, you can identify positive ROI positions. And to kill the rest.
In this example 24 different audiences were tested. Some were more succesful then other
The practice is that you always manage multiple ad creative simultaneously. Some works better then others. Usually, we project the learning from the ad creative to the landing page, as there are things that don’t need to be measured:
Coherent messaging increases CR
When starting, the company was using one long field with many details.
By introducing the two stages form, we enabled to reengage with signups that didn’t complete the funnel.
When we analyzed conversion categorized based on days elapsed since registration, we learn that most transactions happened during the following 72 hours and almost no transaction happened 14 days after transaction. While we wanted to offer discounts to users in order to increase conversion rates, we didn’t want to cannibalize the existing activity. This is why we introduce the time based price differintiation.
Insights:
Time based discount offerings enabled to increase revenue on otherwise wasted leads.
By introducing time based discounts, we managed to take non converting leads that yielded no value into a source of value
Insights:
Increase of average sales price led to drop in CVR but to overall increase in revenue.
Define your business objective: In our case, defining success as new user revenue, and not as conversion rate or merely revenue was dramatic.
Ensure Analytics MVP and remember it’s functionality.
Deploy optimization cycles on all 3 different elements continually