Tokeet: Improving Marketing Data Obstacles for Further Product Success

About the product

Tokeet is a vacation management software for short rentals. Apart from Tokeet, they have several more tools in their product portfolio that are useful for property managers and short rental owners.

Setting up data tracking is always a challenging task, especially when you’re setting it up from scratch, meaning – none of these products had any kind of data setup.

We delved into the challenging project of setting up the complete data tracking and consolidating mar-tech processes for Tokeet and its other five products (Sympl, Automata, Rategenies, Checklist and Signature). 

During the whole process, we collaborated with their development and product management team so everyone would be aligned with the activities and goals we were aiming to achieve.

The challenges

• Sync up with their internal teams (development, product, sales) and understand what metrics they were tracking, and what metrics they wanted to track
• Create a timeline for all the activities to assure everything is delivered on time with no overlaps
• Keep all processes easy to follow even for people not experienced with metrics analysis
• Make the importance of data consolidation for business development easily understandable for the whole team
• Identify all users that are using more than one app from Tokeet product portfolio (e.g. users with accounts on both Tokeet and Sympl)

Main objectives

• 1. Setup all acquisition metrics
• 2. Setup all product metrics
• 3. New Marketing automation strategy – consolidate all email automation sequences, in-app communication and product tours in a logical flow
• 4. Reporting dashboards with actionable acquisition and product insights
• 5. Educate Tokeet product management team how to understand data logic and gather useful insights from reports

1. Acquisition Metrics setup

We started (almost) from scratch with unconsolidated data which were set without any logical order.

Our approach

• We did a comprehensive audit of their current setup
• Sketched out data architecture for future setup
• Created detailed Data implementation plan
• Created timeline for all activities

Results

• Detailed PPC campaign reporting
• Detailed funnel reporting (from website visits → trial form submission → MQL →  SQL →  Customer)
• Customer cohort analysis
• Conversion rates per channel, country, product

2. Product Metrics setup

Even though Tokeet was in the market for a while, they had very little data about how their users are using their product.

Our approach

• We organized brief meetings with product managers responsible for each product from their portfolio and gathered key insights about each product
• Based on their briefs we created an event specification that should be tracked in a product analysis tool (we chose Amplitude)
• We worked on setting the product metrics together with their development team

Results

• Understanding of the overall user behavior
• Onboarding process analysis
• Time to adoption analysis
• Feature adoption analysis
• User segmentation (freemium, trial users, paid customers)

3. Email automation

After a detailed email automation audit, we made two conclusions: 

• 1. Email sequences had a time stamp setup (they sent out emails every two days) when behavioral email sequences would be more suitable
• 2. The tool they were using didn’t support a more advanced email automatization

Our approach

• We suggested using a more advanced email automation tool 
• We created a new email communication strategy 
• We segmented the email sequences according to types of users in the app 

Results

• Increase of 21% in open rate on onboarding email sequences
• Increase of 37% in open rate on post-trial email sequences 
• Increase of 206% in demo call bookings
• Increase of 412% in survey responses from churned or inactive customers

4. Acquisition and Product Reports

We proposed this tool stack for reporting:

Acquisition reports - Google Data Studio, Google Sheets with Analytics API Product metrics reports - Amplitude

Our approach

• We consulted the marketing team and sales team with metrics they want to track
• We consulted the product team with metrics they want to tack within the app
• We created the reporting dynamics – which metrics will be reported weekly and monthly 

Results

• PPC acquisition reports: Conversion stats by channels, campaigns, countries, etc. (conversion rates, conversion costs)
• PPC trend reports: CAC payback, LTV, Signup to conversion time stamps
• Marketing & Sales funnel reports: Stats and numbers by funnel stages
• Product reports: User actions, DAU, MAU, actions by customer segments

Conclusions

These activities took around six months to implement.

These are the overall results. Tokeet now has: 

• Precise insight into their marketing metrics
• Properly segmented users
• Better user behavior tracking

All of this impacted how they acquired new customers and how they communicate with their existing customers, which resulted in higher conversion and retention metrics.

One of the last bits we did is to educate Tokeet product team on how to leverage the data from the new setup.

We organized several sessions where we helped them how to understand their customers by analyzing the quantitive and qualitative data. You can learn more about this here.