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IBM Watson Customer Experience Analytics vs Snowflake Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

IBM Watson Customer Experie...
Ranking in Web Analytics
21st
Average Rating
10.0
Reviews Sentiment
8.1
Number of Reviews
1
Ranking in other categories
Customer Data Analysis (2nd), Customer Experience Management (14th)
Snowflake Analytics
Ranking in Web Analytics
2nd
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
43
Ranking in other categories
Cloud Data Warehouse (11th)
 

Mindshare comparison

As of April 2026, in the Web Analytics category, the mindshare of IBM Watson Customer Experience Analytics is 1.6%, up from 0.3% compared to the previous year. The mindshare of Snowflake Analytics is 2.9%, down from 6.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Web Analytics Mindshare Distribution
ProductMindshare (%)
Snowflake Analytics2.9%
IBM Watson Customer Experience Analytics1.6%
Other95.5%
Web Analytics
 

Featured Reviews

MC
Techincal Pre-sales Specialist - Collaboration & Customer Engagement Solutions at GBM
Great granular DOM level with excellent analytics and reporting
There are three valuable areas: One of them is the granular DOM level where it captures behaviors on the application. Another is the analytics, because you don't need to provide it with a rule to identify the issues, it will analyze the usage of all the customers accessing that site and see if there are any abnormalities and it will identify unexpected changes in the pattern and that there is something wrong that needs to be checked out. That is extremely useful. Finally, the ability to create meaningful reports and dashboards to tell stories. The reports enable you to re-target customers if they've had any problems.
Garima Goel - PeerSpot reviewer
Associate Principal Engineer at Nagarro
Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"You can let your imagination think about a use case and if it's related to customer behavior on the district channels, it can most probably be done."
"The ability to create meaningful reports and dashboards to tell stories."
"The performance has been good."
"Time Travel and Snowpipe are good features."
"The Snowflake features I find most beneficial for data analysis are primarily related to analytics, particularly their features like materialized views and queues, which are especially useful for dashboarding purposes."
"Snowflake Analytics is flexible in nature, allowing for the addition of more data tables without affecting the main structure."
"Snowflake Analytics has played a major role in improving our data model transformations, increasing our productivity by allowing us to do things very quickly and receive results rapidly, and reducing the time and effort required for coding compared to traditional methods and Python."
"It is quite a convenient tool."
"The platform not only provides ease of use but also stands out for its speedy execution, conveying a sense of robustness and reliability that I find appealing."
"The most valuable feature of Snowflake Analytics is its performance."
 

Cons

"The technical side requires development skills during implementation. This could be simplified."
"An area that can be improved is on the technical side where you identify an event."
"The solution needs to consider including some updates in the future."
"If you have a lot of computations, it becomes very costly."
"Improvements are needed in importing and exporting large datasets to and from reporting tools."
"Moving data from legacy systems to Snowflake is not that easy."
"The solution’s interface is good but it could be improved."
"The platform could work easier for AI implementation compared to one of its competitors."
"Improvements are needed in importing and exporting large datasets to and from reporting tools."
"End-to-end execution of jobs isn't possible with Snowflake, which means we have to do some customization."
 

Pricing and Cost Advice

Information not available
"When using Snowflake, you pay based on your usage. They calculate how much CPU has been used. If you use excess warehouse storage, you are charged one credit per hour. If you are in Asia, you are charged $3 per credit. If you have 10 users running parallel with the same excess, you will be charged $30."
"The solution's price is high and I would rate it an eight out of ten."
"I rate the product price a seven on a scale of one to ten, where one is low price, and ten is high price."
"It's not costly if you configure it properly to ensure optimal performance. People don't configure it properly, which is why costs go up."
"The pricing is on the higher side."
"It is not overly expensive. I would rate the pricing a six out of ten, with ten being expensive."
"The cost of Snowflake Analytics is low, any small organization can use it."
"On a scale of one to ten, where one is a low price, and ten is a high price, I rate the pricing a seven. The solution's pricing is high."
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Top Industries

By visitors reading reviews
No data available
Computer Software Company
12%
Financial Services Firm
9%
Construction Company
9%
Marketing Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise13
Large Enterprise21
 

Questions from the Community

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What is your experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
In my opinion, Snowflake Analytics can be improved by introducing more features, such as additional integration options. I remember using Snowflake Pro, which allows exporting direct data into the ...
 

Also Known As

IBM Coremetrics Digital Marketing Optimization aSuite, IBM Tealeaf, IBM Coremetrics Web Analytics
No data available
 

Overview

 

Sample Customers

IMM, Whogohost Ltd., Stonyfield, Grupo WTW, Big Scary Cranium, Brockenhurst College, SiteMinis, RCI Banque Espana
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about Amplitude, Snowflake Computing, Google and others in Web Analytics. Updated: March 2026.
886,174 professionals have used our research since 2012.