Improvado vs. Panoply

This solution helped us when we were stuck trying to explore data deeper and didn’t have enough resources to prepare data for further analysis. The software solves data integrity problems bringing more granularity to all insights. Integration with data visualization tools and well-arranged insights shows how each of the company’s marketing channels performs in real-time. Improvado is also useful for risk mitigation when launching or adjusting marketing strategies. It may also become a valuable tool for businesses, who are aiming at automation and the elimination of routine processes. ETL processes automation unleashes marketing analysts’ potential granting them more time for research of marketing reports.

Panoply is great for smaller organizations where analytics is critical, but it is unrealistic to hire a data engineer or build a data infrastructure. Panoply comes as a full data stack out of the box.

• ETL processes. Once adjusted, Improvado never fails to streamline data from our advertisement platforms to the data warehouse.
• Variety of data sources. Improvado extracts data from over 200 sources, including both well-established platforms and the ones that are rapidly gaining momentum.
• Full-cycle support. Improvado provided us with a dedicated manager available 24/7. Any issues that arose during the product integration were settled in a matter of minutes.
• Flexibility and client-focused approach. After the integration, we adjusted our marketing campaign and needed new ad platforms to be integrated. The vendor allocated the development team ASAP to add new connectors to our existing network.
• Professional services package. The company doesn't provide dashboard views by default. However, we had no time to figure out how to do it ourselves, so we hired a team of Improvado's analysts that set everything up for us.

• Redshift setup -- so much easier with Panoply, rather than messing around with AWS mishegoss
• Automated data ingestion and formatting -- I love not having to write out SQL table schema
• Easy scaling and data warehouse maintenance -- I don't like to have to mess with this in previous redshift implementations

• Improvado didn’t have all the integrations that we needed. However, they offered full coverage and quickly found ways to extract data from the sources we required.
• The user interface for BI tools may be confusing to inexperienced users. Personally, I didn't have any problems. However, some of the junior marketing specialists from my department needed more time to adapt to the UI. Otherwise, the interface is great.

• Needs more user control

It’s a good choice for building a quick, multipurpose data stack for a variety of businesses needs.

We chose Improvado for the following reasons:

• Their data transformation framework cleans, normalizes and prepares data for loading into our data visualization tool;
• We connected our CRM to our analytics tool and as ad account;
• Extensive social media reports - the marketing team can view our ads, posts, comments right from the dashboard.
• Scheduled reports and immediate data sync options help us to get the reports with the most accurate data at the time we need them;
• Google Ads auto-connect new ad accounts.

Our marketing team evaluated Funnel.io and has opted for Improvado because of the following drawbacks:

• With Funnel we’d have to set up an extraction process for each campaign and account manually;
• The more accounts you need to connect or integrations to use, the more you’ll pay;
• Limited data storage options;
• Complicated account export. We had to filter accounts to export through the custom filter rules.

Panoply has much more storage and better organization tools for searching. There are better folders and tools for keeping documents secure and stored for a long period of time. It is better to offload data in mass than singular or Zip drive documents like you would do in Google Drive.

Incentivized

• Increased ROI
• Improved cost of acquisition analysis
• Improved CPA, CPI, CPL report drawing process

• The user interface could use some improvement for analytical tools. Apart from that, it’s great.