Financial explainers and product-path analytics at Sravni
Vladimir RossausContext
Helped turn complex financial topics into readable content and connect social channels to actions in the product.
- Project
- Sravni
- Period
- May 2021 / April 2023
- Area
- Fintech / Media and product
Task
The task and my scope
A loan, insurance policy or banking offer is rarely interesting on its own. Worked on social promotion, formats and analytics alongside editorial and product contributors. The task was to help people understand a topic and see what they did after the content.
Solution
What I changed
Make explanations readable
Cards and infographics split complex topics into short parts. Special projects connected financial questions to everyday situations.
Choose the destination
Matched audiences and destination pages to the topic. The placement promise needed to match the next page.
Build reporting
Connected social and web analytics in dashboards. Followed product visits and agreed events.
Use the findings
Compared topics and formats, continuing those that produced relevant interest and subsequent actions.
Metrics
Key figures
- Relative increase in ER
- +45%
ER: interactions under the agreed formula
- Combined media reach
- 2×
Not a deduplicated audience count
- Stages in the path model
- 4
Content, interest, visit, action
Changes in media metrics
Engagement rate
Combined reach
Chart values
| Metric | Baseline | After the change |
|---|---|---|
| Engagement rate | 100 index | 145 index |
| Combined reach | 100 index | 200 index |
Connecting media to the product
Sequential path example
- 01Saw the content10,000
100% of this cohort · Selected publication reach
- 02Interacted800
8% of the previous stage · Reaction or substantive action
- 03Visited the product240
30% of the previous stage · Tagged visit
- 04Target action36
15% of the previous stage · For example, an enquiry
Reached the last action: 0.4% of entrants
Separating contribution from coincidence
Compare periods and definitions
Keep the ER denominator and interaction set consistent. Account for publication volume, placements and spend when comparing reach. Match topics and audiences.
Check product impact
Connect downstream events to sources. A causal claim about a format needs a test or control group; an overall period increase represents the combined work of the team.
Conclusions
What the work enabled
Higher engagement and reach were complemented by dashboards linking social channels to product visits. This made downstream audience behaviour easier to assess. Sales are measured through separate post-visit events.
The approach at a glance
- Matched formats to the topic and audience
- Connected reach, visits and subsequent actions in reporting
- Assessed media alongside the product team
Working on a similar task?
Share the product and the change you need. We can discuss my scope, the available data and a next step.
Discuss the task