Acoustic Analytics (formerly IBM Watson Customer Experience Analytics) vs Apache Solr

• Tealeaf provides a unique view into a website beyond what typical web analytics can provide.
• It captures all of a website's traffic, no need to tag pages or decide ahead of time what data you want to capture.
• Data is captured and processed in real-time which reveal unknown issues as they are happening.
• Replay session to see what a customer or user actually did and not just they remember doing when a problem occured.

Read full review

• Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
• Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
• Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.

Read full review

• More knowledge sharing sessions
• UI/UX Improvements
• More tooltips on icons

Read full review

• These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
• We have lot of classifications and lot of data for each classification. This gave us several problems:
• First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
• Second: We needed several load balanced Solr databases.
• Third: We needed to update all the databases and keep old data status.
• If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.

Read full review

• The ROI question needs to be focused on clients and not our use internally. We leverage this as a platform for designing customer journeys for our clients.
• The ROI case is far easier to make for eCommerce operators. Customer journey failings can be easily quantified and seemingly simple issues can generate large ROI outcomes. For web assets without a trading bias, ROI can be established using notional value attribution. For example, a lead for motor insurance that is lost can be costed based on average policy value over a typical lifetime; struggle on a customer self-service portal can be quantified on the cost of handling through a call centre; etc.

Read full review

• It's enabled us to deliver fast, relevant search results on our new website. The site is still in beta and being actively developed so our complete ROI is still unknown.
• It integrates very well with Drupal so it has saved us from having to develop a custom solution.

Read full review