Well suited: 1. If data set is not yet well organized. 2. Hypothesis is not yet established. 3. Need to visually explore to find patterns of data (often when analysts have no good understanding of data) 4. When [you need] to analyze events with a timeframe (specifically a sequence of events as a transaction) Less appropriate 1. If a data set is very large, such as Hadoop data, it becomes hard to manage data pipeline and process to feed the data into Ayasdi. To be feed into Ayasdi, data should be aggregated or organized to some level.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
This is the only forecasting tool you need. Best for CSMs renewal forecasting. Can even forecast churn as far out as you'd like. Example: we forecast 3 quarters out (even if it's just a rough guess). Helps ELT determine OKRs for H1 & H2. Best for Sales for net new opps or existing customer expansions. We're able to segment and see that mid market is closing more deals in a specific tool than enterprise and can segment down by industry or AE/CSM to see what's working and what's not
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Ayasdi Core provides an easy way to get some insight on data. Typically analytics may require having a model or hypothesis before starting to look into the data, but Ayasdi lets you just feed the data first then start seeing what the data looks like.
Ayasdi Core's topological network visualization is quite unique. It allows you to explore patterns and potential relations between multiple data elements. A user can also dynamically navigate data with different aspects on the web.
The Web version of Ayasdi is easy to use, stable, and fast. It hasn't crashed even when we feed it a lot of data sets, although it took time.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Use of Python SDK is required to feed data into Ayasdi, but it lacks training materials or sample codes for a novice to get started.
Although Web UI of Ayasdi is looking good, often it freezes when the user runs an analysis. It doesn't crash but the web page needs to be refreshed to see the progress of analysis.
Algorithms provided by Ayasdi, such as metrics types, lens types need to be explained (what they are and what their strengths and weaknesses are). We had to Google or do research on our own to understand what they are.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Occasionally it can be difficult to save specifically formatted criteria views
The QBR dashboard has a lot of information on it, would be helpful if that was simplified to show what is most important
The Salesforce integration is not immediate, so when updating opps it can take Clari 10-15 minutes to accurately reflect (but honestly still works great)
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I will renew my Clari Subscription for many reasons. 1. Streamlines Sales - Clari automates many manual tasks like note-taking and transcripts. This frees my sales team so they can focus on closing deals. 2. Increased customer retention - Clari helps me identify potential churn risks and take proactive measures. 3. AI-Driven Insights
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Because i never had issues with using the product it is more that the departments that need to set up all fields for the sales teams can use more training and guidance to quickly get the right results using Clari
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Clari is very willing to jump in and build out use cases. They will work to do anything for you. That said, their follow up is not great. We have had to reach out for follow up several times on a project, which is still not complete. I wish they taught us how to complete what we want, rather than doing it in house for us
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We had a working group that has been using R studio for the general purpose of statistical analysis in our organization. Although it is a great tool that provides enriched function sets, it is time-consuming for our clinical analysts to learn the tool to see the first result. R is somewhat of a developer-oriented/friendly tool. Ayasdi is friendly to a domain analyst or end users. Plus, support and consulting from Ayasdi were excellent so that we could get knowledge from them immediately whenever we needed.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
At the time of selection, Clari was a more mature product than Xactly Forecasting. We did not want to experience growing pains with Xactly. Pipeline Inspection from SFDC was just becoming available. We had already selected Clari before we learned about Pipeline Inspection.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Clari is worth the investment with its advanced forecasting and pipeline management. They have a unified revenue platform that serves as a single source of truth for revenue data.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
