IBM Watson Explorer supports enterprise search with unstructured data analysis, machine learning, and content analysis to improve decision-making, support customer service or serve other business needs.
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Searchspring
Score 9.0 out of 10
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Searchspring headquartered in Denver offers intelligent site search for customer facing web pages and ecommerce, providing product discvoery tools, navigation viacategory page, and other features to improve site navigation.
In February 2020, Searchspring merged with Nextopia to expand its product capabilities, and customer base. Nextopia customers will continue to receive the same services, under the SearchSpring brand.
The Watson Explorer is great because it potentially replaces a meriad of other low-level analytics products that we would need to use for data analytics and data mining. WEX isn't really suitable much beyond doing text and data analytics and performing machine learning, so if your team doesn't really have a use-case that fits all of these categories, it is worth looking at an alternative.
Search Spring offers strong options for search customizations: synonyms, redirects, query replacements, spell corrections, etc. We enjoy the ability to boost and unique product display options. We were 4Tell customers prior to the Search Spring acquisition and we're looking forward to both being part of one console. Search Spring is a really solid, stable search/merch platform that I would recommend for any mid-market business.
Free to try - It's possible to use most of the useful features of Watson Explore on their trial/demo accounts.
Super well-designed data analytics tool - Most of the tools and features of the explorer are really useful, and truly help you fully understand the depth of any format of textual data.
Extensive sources compatibility - WEX can retrieve data from a large range of sources, and the compatibility there is quite good as well.
Support is just OK, like most of the other IBM Watson products. The setup/integration is really hands-on, but it's also problematic because support later may take a considerable amount of time.
UI could still use a little more improvement - part of the administration and sources dashboards are hard to navigate.
The Application Builder is a great part of the product, but hard to learn/understand - this is where we needed the most support from IBM and tutorials/documentation.
Developing 'cocktails' of different ranking criteria. At the moment we can only serve results based on either 'relevancy' or 'sales performance'. It would be great to not only have the ability to blend these two options (by search term), but also add additional facets into the mix, such as stock quantity, margin, sponsorship factor etc...
Provide financing reporting on results - so we know how much revenue/conversion has been driven from specific search terms. For example, "Baby Milk" drove 50 searches, 6 direct conversions (customers that searched went on to buy an item(s) that were recommended), 16 indirect conversions (customers that searched went on to buy other item(s) not severed).
We have a monthly phone call with our account manager, and she is available for calls in between as well. She has always been accessible. Working with her has been easy and she has provided training where needed. She is proactive in making sure we have everything we need and feel comfortable with the platform.
Google Cloud offers a Natural Language product, but it is just an API. This API doesn't offer the useful visualizations of relations, analytics, and graphs that IBM Watson Explorer offers on their interface. For this reason, we chose to go with IBM WEX. For later stages of our production, we decided to use Google's NLP API because we found that it was quick to integrate into production after studying data and developing models using IBM WEX.
Nextopia’s features were on par or better than consideration set at a lower cost and with an easier implementation. Contract terms were also more favorable.
Positive - Trial/demo period. This was really useful for us to figure out what features of WEX we liked most and how difficult it would be to integrate WEX into our workflow.
Negative - On-boarding was long and almost always requires support from IBM support, unlike most other products this advanced.
Positive - WEX replaced a large selection of alternative products we would have to use for the same functionality, and having all of that function in one place was definitely helpful.
