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Blitzllama vs Clevertap vs Typeform vs Hotjar

A quick, unbiased comparison between the 4 popular tools used by product teams in fast growing companies to conduct in-product research.

August 5, 2022
Rahul Mallapur

Use cases in customer-informed companies

The fastest growing tech companies like Slack, Doordash, Canva, or Snowflake are customer-informed. In these companies, listening to customer issues is the responsibility of not only the customer success and user research teams but also that of the leadership, engineering, and product teams.

Product Teams

  • Generate and monitor actionable insights in real-time from existing feedback prompts of D30 NPS or app review.
  • Know what users think about the recent feature launch at scale i.e. ask questions to users immediately after using the feature.
  • Prioritize top customer issues for the next sprint. Ideally have cohort-wise visibility to assess revenue and engagement impact.
  • Understand why users are churning at a specific stage in the product journey i.e. ask questions to users after churning from a product stage.
  • Share feedback charts in the weekly product update email or the Townhall meetings to align the rest of the team without putting hours of effort to dig data and beautify charts.
Monitor feedback trends | Auto-generate insights | Prioritize customer issues by user cohorts | Ask questions to the right users at the right time | Share charts to align teams

User Research Teams

  • Conduct high-quality feedback studies without taking time from the engineering, product, and data teams. And without new app releases for each study.
  • Run different types of user studies like quantitative surveys, design studies, etc.
  • - Analyze the feedback data quickly and without involving the data teams.
Conduct studies quickly without requiring app changes | Configure different studies | Ease of analyzing data

Leadership Team

  • Monitor customer satisfaction ratings across platforms
  • Access the top positive and negative customer issues easily
  • Feedback highlights of recent feature launches, research studies, and growth experiments.
Monitor customer satisfaction ratings | Access top customer issues | Feedback highlights

Data Teams

  • Analyze feedback data to build hypotheses, ideally combining quantitative events data with the qualitative feedback data.
  • Create dashboards by using various filters and user metrics for product, growth, and leadership teams
Analyze feedback data to build hypothesis | Create dashboards for other teams

Evaluation criteria


  1. Configurability: Edit and launch surveys easily, across platforms, and without engineering effort or app release.
  2. Target the right users: Control which users get the surveys. Moreover, the user attributes and cohorts should be synced across the product stack.
  3. Target at the right time: Show the survey right after a user completes an action. In-the-moment surveys generate highly contextual feedback data and high response rates.
  4. Superior UI/UX: A no-brainer, designs should be customizable to your product’s UI/UX.
  5. Multilingual support: Users should see the survey in their language. And the teams should be able to learn from all multi-lingual users as well.
  6. Guardrails: Your users’ experience should be protected i.e. same users should not be surveyed frequently. etc. Also, the collected data should be free of any biases.


  1. Minimal time to insight: Time spent on categorizing feedback data (including processing multilingual data) should be zero.
  2. Observability: Every team can monitor the relevant feedback trends - top customer issues for product teams, NPS for strategy teams, stability dashboards for engineering teams, etc.
  3. Analysis: Conduct deep dives on feedback data. Especially useful for product and data teams.


  1. Sync user data: Easily connect to tools across the product stack to make sure the same user cohorts are analyzed across the tools.
  2. Post-feedback workflows: Filters the collected feedback data and push it to relevant platforms and tools like Slack, Amplitude, or your databases.

Integration impact

  1. Low engineering effort: Minimal time to integrate and test. Multiplatform availability is a huge plus.
  2. No impact on app performance: There should be no stability issues and no increase in app size or loading time.
  3. Access & Usability: Simple-to-use dashboard makes Blitzllama accessible to non-product/engineering teams as well.

Comparing Clevertap, Typeform, Hotjar, and Blitzllama


Clevertap is a cross-platform, all-in-one product engagement platform offering push notifications, in-product nudges, and product analytics. Clevertap has similar offerings to Pendo and Braze .

Clevertap is one of the most adopted product engagement tools in India, SEA, and LatAm.

Clevertap’s configurable in-product dialogs can double up to collect targeted in-product user feedback.

So how does Clevertap fare?

The good parts 🥳 😎

  • Easy to configure: Once Clevertap is integrated into the mobile or web product, feedback prompts can easily be edited and launched from Clevertap’s dashboard.
  • Target the right users at the right time: Clevertap has native support for capturing user events and attributes. These can be filtered to target the right users after they complete actions. Further, one can import user cohorts from third-party tools like Mixpanel to target users in Clevertap’s feedback prompts.
  • Effortlessly import user data from third-party tools: Clevertap has one-click integrations with popular attribution, remarketing, analytics (only Mixpanel), and customer data platforms to import user attributes and cohort data.

The bad parts 😞 😩

  • No guardrails to protect the user experience: There is no way to stop the same users from being surveyed multiple times or no opt-outs of feedback campaigns. Too many frequent feedback prompts can lead to a bad user experience.
  • Non-native UI/UX: Clevertap Android and iOS feedback prompts have HTML-based UI, which allows for high customizations but a non-native app look.
  • Limited multilingual support: Surveys can be launched in multiple languages, personalized to users’ preferences. But there is no auto-translation of user responses. And manually translating responses takes hours - probably why most teams never run multilingual surveys and only hear feedback from English users.
  • Takes hours to generate insights: Lack of text summarization and limited filters to slice and dice the qualitative feedback data implies that teams have to download feedback data into excel sheets and map to quantitative data to conduct analysis.
  • Limited observability and analytics: Although Clevertap has good support for creating dashboards for quantitative data but none for qualitative data. For example, one cannot create a dashboard of top customer issues for roadmap prioritization.
  • No post-feedback workflows: One cannot filter feedback data from Clevertap and send it to tools. For example, sync low NPS feedback to Intercom for customer support teams or bug reports to the Slack engineering channel.
  • Hard to use for non-product/growth folks: User researchers, designers, and leadership teams face friction using Clevertap as the dashboard UI is very complex. Due to a lack of user experience guardrails, growth teams create multiple processes and checks to run a feedback survey i.e. a user researcher may have to build a case and involve the growth manager, data analyst, and product manager to run a single survey.
  • Pay for the entire suite: To run feedback collection on Clevertap, one has to buy the entire suite which includes push notifications, in-product nudges, and feedback collection. Clevertap doesn’t have freemium or self-serve. The MAU-based pricing is also not aligned with the usage and value generated from feedback.
“We (user researchers) could never get to use Clevertap for in-product user research because Clevertap was designated for marketing and growth teams to use, and we rarely for signoff to use”.

- User Researcher, Betterplace

“Monitoring and analysis of the feedback data are hardly possible in Clevertap. This limited our use cases to only NPS and the teams that can use Clevertap” .

- Lead Product Manager, Vahan


Typeform is one of the most beautiful and easy-to-use survey tools out there. It has extensive support for survey use cases of launching multiple question types, customization, and integration with other tools.

Most commonly product, growth, and user research teams embed Typeform survey links inside app banners or popups.

So how does Typeform fare for product feedback at scale?

The good parts 🥳 😎

  • Easy to configure: Surveys can be edited, customized, and launched from Typeform’s dashboard easily. Although embedding survey links inside app components needs developer intervention and sometimes app releases.
  • Superior UI/UX but leads outside the product: Typeform has some of the best customization features, but the surveys open outside the app in a web browser that gives the surveys a non-native look. This significantly reduces the fill % and users returning to the app.
  • Good post-feedback workflows: Typeform connects with 100+ third-party tools (3k+ with Zapier), so it is super easy to push feedback data into your favorite tools within few clicks.

The bad parts 😞 😩

  • Cannot ask questions at the right time to the right users: Typeform doesn’t have a cohort or event-based architecture, so one cannot display surveys to specific users after they complete certain events. Instead, survey links have to be embedded into existing app banners or dialogs, which makes it hard to control which user sees the survey and when.
  • Limited multilingual support: Typeform supports multiple languages but each survey can only have one language. Multiple surveys lead to storing data in multiple sheets. Further, language personalization has to be built on the product’s end i.e. the app has to serve a Spanish survey link to a Spanish user and a Hindi survey to a Hindi user.
  • No guardrails: There is no support for managing user experience without web and mobile SDK natively launching the feedback prompts.
  • High time to insight: No auto-summarization of textual responses increases the time taken to generate insights. Further multi-lingual responses have to be manually translated.
  • No monitoring abilities: One can't create Amplitude/Tableau-like dashboards as Typeform is meant more for data collection than analysis of the feedback data. Hence lacks capabilities to create custom charts or a single repository to visualize all feedback data.
  • Limited analysis capabilities: User data like cohorts or attributes cannot be imported into Typeform, hence quantitative + qualitative analysis is not possible. Further, there is no single repository for all the survey data which limits many use cases such as prioritization of user issues across surveys, etc.
“We used Typeform surveys because it is very convenient to launch. The two tradeoffs were lack of targeting which reduced accuracy off collected data and users moving out of our website to fill the survey.”

- Product Lead, smallcase


The super popular Hotjar recently rebranded its feedback collection features as the Ask product. Ask has two modes to collect feedback: Feedback that is continuously visible on a website, and Surveys to launch targeted feedback prompts.

So how does Hotjar Ask fare?

The good parts 🥳 😎

  • Configarability: Hotjar provides always-on and targeted feedback prompts. The questions, conditions, and targeting is configurable without coding. Hotjar provides survey templates that make it simpler for all teams to ask the right questions.
  • Highly customizable: The colors, branding, and positioning of the feedback prompt can be customized right from the dashboard and without any app releases.

The bad parts 😞 😩

  • Cannot target mobile users: Hotjar only supports web applications and cannot be used to launch feedback prompts for mobile applications. User attributes can be used to target web users. These user attributes can be created on Hotjar but cannot be imported from third-party tools like Segment, Mixpanel, etc.
  • No data import or native-export integration: Cohorts or segments from third-party tools cannot be imported to Hotjar. There is data export support but via Zapier to tools like Mixpanel and Salesforce. But integration via Zapier works out to be super costly at scale.
  • No language personalization: A feedback prompt can have any of the 40+ languages as the default language. But language cannot be personalized as per user preference. The non-English feedback responses are not translated to be included in the word cloud analysis.
  • No user experience guardrails: There is no support to limit surveys a user sees among other things, which are super important to protect the end-user experience.
  • Analysis limited to word cloud: The textual insights are summarised into a word cloud and do not capture the true sentiments and semantics. More importantly, cross-survey analysis such as "how many people faced the blur out bug" is not possible.
  • Limited observability: Custom charts using various filters of user events and attributes across the feedback data is not possible on Hotjar.
  • Super pricey: Hotjar Ask plan starts at $64/month for up to 500 monthly responses. The price scales with the response collected every month.


Blitzllama is built to serve the needs of fast-growing customer-informed companies. The intuitive UI and low-code setup makes it easy for all teams to launch in-product studies and analyze the feedback data.

How does Blitzllama fare?

  • Configure without app releases: It only takes 30 mins to fully integrate Blitzllama into a mobile app or website. Once integrated, micro surveys can be created, customized, and launched into multiple platforms from the dashboard without any app releases.
  • Survey templates: Templates on the most common use cases make it simpler to ask the right questions.
  • Target the right users at the right time: ]Filters on user attributes and cohorts enable showing the survey to the right users. With event-based architecture, users get surveys immediately after completing an action or an event inside the app.
  • Superior and customizable UI: Colors and positions of the feedback widget can be customized from Blitzllama’s dashboard to match the product’s native UI.
  • User experience and data guardrails: There are user experience checks to ensure that the same users are not surveyed repeatedly or not caught at the wrong time. While data guardrails provide options to auto-pause surveys on hitting statistical confidence and so on. Guardrails are important to protect the user experience and improve the quality of decisions.
  • Auto generates actionable insights: Advanced NLP algorithms sift through textual data and categorize each response - creating themes, sentiments, and recommendations.
  • Easy to conduct analysis: A single repository storing all the feedback data along with a UI-based query builder makes it easy for non-data teams to analyze data across surveys.
  • Create custom dashboards: One can create Amplitude/Tableau-like dashboards for all teams to continuously monitor the relevant feedback trends in real-time.
  • Value-aligned pricing: Pricing is based on the number of responses collected, which is more aligned to usage and value generated, than pricing based on monthly active users.
  • Easy-to-use dashboard makes it simple and intuitive for all teams to actively use Blitzllama.