Dexi.io with Mozenda vs. Gavagai

The Mozenda platform is well suited to some specific scenarios that may work well for your organization. It is especially helpful for basic scraping of information from simple websites. If the information you need to obtain is clearly stated on a website, then Mozenda is a simple solution to capture that data quickly and easily.

Incentivized

Gavagai is well suited for a B2C business that receives a lot of customer feedback in a form of open-ended text. It makes life easier for the customer experience team to efficiently identify the strengths and areas of improvement for the business. It saves a lot of time and also the hassle of analysing text data manually. It is not just a word cloud tool that shows you the words with the most number of mentions. Gavagai directs you towards actionability.

Incentivized

• Action Items. Mozenda is broken down into a series of actions that can be performed on a page. Some actions take you to other pages. The action list, while short, provides a comprehensive set of tools for scraping just about any website (I haven't met one where it didn't work yet).
• Error Handling. I've used some scraping tools that have virtually no error handling. Mozenda has great error handling; the software almost always pinpoints the exact action where the agent failed and why.
• Speed. Mozenda is very fast at obtaining results. Other "bot" software can be slow and cumbersome but Mozenda plows through pages rapidly and accurately aggregates information.
• XPath compatibility. One of the most powerful features of Mozenda is the integrated ability to use XPaths to get at the exact bits of information we're after on a particular website. Access to visible information is only limited by imagination.

• Simplifies text data.
• Lets you customise your dashboard.
• Sentiment analysis
• Supports 47+ languages

Incentivized

• The user interface for managing agents can be improved
• When websites change, the agents could be better at dynamically updating
• The "credit" usage can be confusing

Incentivized

• Auto generated filters based on the data uploaded.
• Adding more Indian regional languages.
• Competitive pricing

Incentivized

I'm only personally experienced with UBot Studio and Scrapy. UBot Studio isn't a bad application, though it has quite a large number of bugs when compared to Mozenda. UBot touts itself as low-code, but requires a significant understanding of programming logic to use the program effectively. Using UBot, we were able to get virtually all the results we wanted, but at a much higher labor cost than Mozenda. During initial implementation of UBot, it took me a full week to develop a particularly complicated agent. Using Mozenda, I was able to recreate the same agent in 4 hours. The ROI has been remarkable, and Mozenda really is a low-code platform.

I didn't evaluate many options while choosing Gavagai, I had explored a few local vendors whose capabilities were either incomplete or were not up to the mark. Their customer support was also quite poor. Also, the tool was debugged enough which led to frequent crashing. Alchmer although is not a direct competitor to Gavagai, since it's more of a customer feedback tool with additional capabilities of text analytics. I found Alchemer to be extremely expensive. Zonka on the other hand was quite welcoming to feedback from me and promised to develop additional capabilities for my specific requirements although the plan didn't go through due to internal reasons.

Incentivized

• Stay relevant in the market
• Ensure product placement against competitors
• Dramatically enhance profitability

Incentivized

• Helps save man hours.
• Reduces the effort required to analyse big data.
• Helps to act upon areas of improvement faster.
• Indicates the strengths or things that are particularly liked by your customers.

Incentivized