Top 3 IBM Watson Competitors Under $2,000 in 2023

A “good” user experience increases conversion KPIs by 80%.

So providing a seamless customer interaction could be one reason behind companies investing in conversational AI platforms. And IBM Watson is one of the widely-used platforms for automating customer service and customer interaction.

However, no tool is perfect. Our research has identified a few negatives users have had with IBM Watson, mainly that it is:

• Too expensive for SMBs
• Data-heavy
• Lacking in analytics

In this article, we will evaluate IBM Watson in more details, and look at 3 alternatives that could be better aligned with your business needs.

IBM Watson Review

To automate customer interactions, IBM Watson offers:

Based on IBM’s analysis, its conversational AI platform provides a:

• 370% ROI
• 95% response accuracy
• 24/7 reliability

A) Ratings

• AIMultiple: 4.4/5
• Gartner: 4.5/5
• G2: 4.4/5
• Trust Radius: 8.7/10

B) Pricing

Version	Pricing/month	Features
Lite	Free	– Handles 1,000 users/month – Offers 3 bots – Stores analytics data for 7 days – Holds a 5-minute timeout
Plus	$140	– Handles +1,000 users/month – Offers 10 bots – Stores analytics data for 30 days – Holds a 24-hour session timeout limit
Enterprise	Customized	– Handles +50,000 users/month – Offers 30 bots – Stores analytics data for 90 days – Holds a 7-day session timeout limit

C) Pros of IBM Watson

• Ease of setup: Bots can be created with little programming knowledge¹

• Wide applicability: Besides lifelike conversational interactions, it can execute rule-based tasks²

• Integrability: It can be integrated into different platforms³

D) Cons of IBM Watson

• Data heavy: The tool needs lots of data for model training, not all of which can be easily created⁴

• Expensive: The cost can add up for large companies that need a scalable solution⁵

• Lack of analytics: The analytics feature might offer limited insights to business users[/efn_note] Gartner. [/efn_note]

Why look for IBM Watson alternatives?

You should look for IBM Watson alternatives if you

• Find IBM Watson’s pricing to be high
• Want a less data-heavy solution
• Need advanced analytics

We narrowed our search to solutions that matched IBM Watson (i.e. easy to set up, flexible, integrable), but without its shortcomings. Our shortlist for IBM Watson Assistant alternatives is:

• Haptik
• Kore.ai
• Google Dialogflow

	Haptik	Kore.ai	Google Dialogflow
AIMultiple	4.5/5	N/A	N/A
Gartner	4.4/5	4.7/5	4.2/5
G2	4.5/5	4.7/5	4.3/5
Trust Radius	N/A	7.6/10	8.1/10

Haptik

Haptik’s conversational artificial intelligence software offers highly engaging user experiences across numerous industries, and is integratable with:

• WhatsApp
• Instagram
• Webchat, and more.

Haptik offers:

• Prebuilt conversation workflows
• NLP for automatic speech recognition
• AI-powered live agent assistants for lifelike conversational interactions
• Multilingual assistants
• Campaign bots
• No-code setup
• User dashboard for predictive analysis and predictive analytics

Pricing

Haptik’s 3-tier pricing starts at $416/month. It seems to be more expensive than IBM Watson, but offers 16,000 conversations/month.

Pros of Haptik

• Analytics dashboard: The analytics dashboard offers business insights, usable by data scientists to fine-tune the chatbot⁶

• Simple setup: Haptik’s no-code engine enables a quick and simple setup⁷

• Data-efficient: Users haven’t labelled Haptik as “data-hungry.” It can be run with an “efficient” amount of data fed into it⁸

Cons of Haptik

• Sporadic misunderstandings: The automatic speech recognition feature can sometimes malfunction⁹

• Slow response time: The support response can periodically be slow¹⁰

• Lack of integration: Haptik’s chatbot can sometimes not integrate well with other products, like WhatsApp¹¹

Kore.ai

Kore.ai is another one of IBM Watson’s top alternatives. Their chatbot and virtual assistants are powered by a no-code, flexible architecture usable by citizen developers and professional programmers alike.

Pricing

Kore.ai has a Standard (conversation-based) and an Enterprise (session-based) plan.

The Standard plan costs $0.2/session, chargeable at $100 intervals, equalling 500 conversations. The Enterprise plan, on the other hand, has customized pricing model.

Pros of Kore.ai

• Data-efficient: Kore.ai can be set up and utilized across multitude of use cases with a small amount of training data¹², ¹³

• Detailed documentation: The trainings and documentation are detailed and easy to learn for users ¹⁴

• Analytical dashboard: Kore.ai’s dashboard offers detailed data, including the analysis of user sentiment¹⁵, ¹⁶

Cons of Kore.ai

• Confused self-service: The chatbot doesn’t work well autonomously. It needs a human-in-the-loop¹⁷

• No integration with external databases: Kore.ai doesn’t connect with external databases for retrieving information¹⁸

• Too many updates: Chatbot receives too many updates, making retrieval of older versions impossible¹⁹

Google Cloud Dialogflow

Google Dialogflow can be used to create chatbots, voice assistants, and virtual assistants, all of which can be integrated with different conversational platforms, such as:

• Google Assistant
• Twitter
• Slack
• Telegram
• Facebook

Data scientists can use its no-code interface for:

• Model training
• Designing conversation flows
• Defining intents

Pricing

Google Dialogflow comes in 2 packages, CX agent and ES agent. CX is usable for large companies, ES for small ones.

CX agent costs $0.007 per text request, the ES agent $0.002. Therefore, to run 16,000 requests/month (the same amount as Haptik offers in their base package), it costs:

• $384 annually for the ES agent
• $1344 annually for the CX agent

Pros of Dialogflow

• No-code: Same as other chatbots on our list, Google Dialogflow’s no-code base simplifies bot set up²⁰

• Easy to train: Training the chatbot can be straightforward, whereby the generative AI uses the input to create the replies²¹

• Analytics: The visible dashboard provides detailed insights and analytics which helps with the unsupervised running of the bot²²

Cons of Dialogflow

• Lack of documentation: Documentation, especially Python-related ones, can be deficient²³

• Limited customizability: Customization can be limited, often dragged down by the no-code framework²⁴

• Limited keyword breadth: There’s too much reliance on exact keywords, and a weak NLP engine²⁵

For more on chatbots

To learn more about chatbots, read:

Download our comprehensive conversational AI whitepaper:

Get Conversational AI Whitepaper

Transparency Statement:

AIMultiple collaborates with many technology vendors including Haptik.

Sources

1. G2.
2. TrustRadius.
3. Gartner.
4. TrustRadius
5. G2
6. G2.
7. Gartner.
8. G2.
9. G2.
10. Gartner
11. Capterra.
12. Gartner.
13. Gartner.
14. G2.
15. G2.
16. Capterra.
17. Gartner.
18. G2.
19. Capterra.
20. Gartner.
21. Capterra.
22. Gartner.
23. Capterra.
24. G2.
25. Capterra.

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