Hotjar has long been a go-to solution for web product managers and designers seeking to understand user behavior through heatmaps and session recordings. However, when it comes to collecting in-app feedback and analyzing it effectively, Hotjar’s capabilities are found lacking. This is where Blitzllama enters the scene, offering specialized tools for modern product and user research teams, making it a robust alternative. In this blog post, we take a deep dive into the features and benefits of both Hotjar and Blitzllama to see which tool stands out in various feedback-related scenarios.
Hotjar: An Overview
Hotjar is a product experience insights tool that combines behavioral analytics with feedback data to understand user behavior on websites.
Hotjar offers a suite of features including Heatmaps and Recordings, which provide visual insights into how users interact with pages. Additionally, Surveys and a Feedback widget enable direct user engagement.
Hotjar's Dashboard and Trends facilitate tracking key metrics and identifying trends over time, while Highlights and Collections aid in organizing insights for team analysis.
Unlike traditional analytics tools, Hotjar provides a more comprehensive understanding of how and why users interact with your pages, offering actionable insights for site improvement. Its Session Capture feature automatically records user sessions, obviating the need for manual data collection and providing continuous insights.
Blitzllama: An Overview
Blitzllama makes collecting and analyzing accurate product feedback much faster. It is specifically designed for product, research, and growth teams.
With targeted in-product surveys, you can effortlessly ask questions of users at any stage of their product journeys, obtaining results in hours instead of weeks. In-the-moment surveys yield highly contextual feedback and produce average response rates of 35% – ten times that of email surveys.
Blitzllama's GPT3-powered feedback analytics instantly categorize and translate feedback into topics, sentiments, and recommendations. This saves hours spent on categorizing feedback data. Furthermore, all feedback is stored in a single repository, allowing you to segment historical data and build dashboards.
Let’s compare Blitzllama and Hotjar across three common feedback use cases for product and research teams.
Usecase #1: Measuring customer satisfaction at critical product stages
Measuring customer satisfaction at critical product stages, such as post-onboarding and post-transaction, allows product teams to monitor trends and detect shifts in customer sentiment. This helps in understanding the impact of product modifications or enhancements. It is a vital tool for product teams as it provides contextual insights and serves as a measure of the success of product initiatives in real time.
Combining customer satisfaction ratings with open-ended questions yields a deeper understanding of customers' experiences with the product, guiding targeted improvements. Moreover, customer feedback, which captures personal experiences and distinct challenges, offers insights beyond what analytics alone can achieve, empowering teams to address customer issues effectively and enhance satisfaction.
Important considerations for implementation:
1. Web and mobile presence
Hotjar only supports web-based products and is not compatible with mobile apps. Blitzllama supports both mobile and web products and ensures that a user does not receive the same survey on both mobile and web.
2. Customization of UI/UX
White labeling and customizations are available in Hotjar’s Business and Scale plans. Similarly, these features are available in Blitzllama’s paid plans, which are at least 50% more affordable than Hotjar’s. Hotjar’s Business plan costs $289/month for 5k responses and $99/month for 1k responses. Blitzllama offers a flat subscription based on monthly active users with unlimited monthly responses. For comparison, Blitzllama costs $50/month for a product with 25k monthly active users (https://blitzllama.com/pricing) and provides unlimited responses, saving you at least 50% compared to Hotjar.
3. Frequency of surveys
Hotjar doesn’t provide control over how often a user should be surveyed, so it’s highly likely that a user would receive multiple Hotjar surveys in a single session.
On the other hand, Blitzllama has extensive resurvey controls that allow you to display a new survey based on when the user last viewed the previous survey, and control the frequency of resurveys.
4. Ease of data analysis
Hotjar launched AI-powered survey summaries last month. You can summarise the results to highlight notable findings, quotes, and recommendations for the next steps.
Similarly, Blitzllama uses GPT to categorize all feedback into topics, sentiments, and urgency.
Blitzllama takes it a step further by enabling you to create shareable dashboards and maintaining all feedback data in a queryable, single repository. More on this in #3: Diving into historical feedback.
5. Personalization and translations
Hotjar has limited or no support for personalization and translations. Since Blitzllama is tailored for product teams, it allows you to personalize your question texts with user attributes or event data. For example, “Hey John! How would you rate your KYC process?” uses the user’s name for personalization and hence achieves higher response rates.
Additionally, you can personalize the survey language based on the user’s preference, so a Spanish user will see Blitzllama’s survey in Spanish, and a French user will see the survey in French. Blitzllama also automatically translates the responses into English, while retaining the original response, to facilitate faster analysis.
Usecase #2: Ad-hoc product research
Product and user research teams often have pressing questions, such as why users are dropping off on a particular screen or what problems they want to be solved next. In-product surveys enable you to obtain highly accurate answers to these questions quickly and at scale.
Important considerations for implementation:
1. Web and mobile presence
As mentioned earlier, Hotjar lacks mobile compatibility, while Blitzllama supports both mobile and web platforms.
2. Targeting specific cohorts of users
Hotjar integrates with popular product analytics and engagement tools like Mixpanel, Segment, and Google Analytics. However, these integrations only support syncing events from these tools, not cohorts.
Blitzllama offers similar no-code integrations with popular analytics and engagement tools but also supports syncing cohorts. This makes launching Blitzllama surveys to specific cohorts seamless.
3. Event-based surveys
Building on the previous point, Hotjar supports event-based triggers, enabling you to show a survey to a user right after they complete an event, collecting highly contextual feedback. Blitzllama offers similar support but lags behind Hotjar in terms of integration with productivity and marketing tools (which are not critical for product and user research teams).
4. Quick survey design
Both Blitzllama and Hotjar feature AI-powered question assistants that help you frame unbiased and insightful surveys quickly. However, after testing both assistants, we found that Blitzllama creates more contextual surveys. This is because Blitzllama’s question assistant continuously trains on your data, ensuring that taxonomy and context are more aligned.
5. Data guardrails
To help you make decisions based on accurate feedback, Blitzllama offers features to clean your response data, such as filters to remove spam, low-intent feedback, and accidental clicks. It also offers statistical confidence indicators to help you choose the sample size and pause surveys. Hotjar lacks these data quality control features.
Usecase #3: Diving into historical feedback
Storing historical survey feedback data in a single repository is crucial for ensuring a comprehensive understanding of user perceptions over time. Centralizing this data enables efficient analysis through automation, allowing for easy identification of trends and patterns. Additionally, it promotes enhanced collaboration as teams across an organization can access and share insights, which are invaluable for informed decision-making and product development. This repository serves as a system of record, making insights readily available and self-serve, contributing to the organization's agility and effectiveness in responding to user needs and preferences.
Hotjar has limited or no support for feedback analysis and suggests the manual analysis of the data. Let's dive into what Blitzllama offers.
1. Single feedback repository
Blitzllama stores all feedback data across surveys (with support for external sources like app store reviews coming soon) in a single searchable repository.
2. Searching across feedback data
You can perform a quick search for “users who are facing withdrawal issues” in the repository and retrieve all customer comments across all surveys.
Additionally, a graphical query builder provides various filters to analyze different types of feedback by cohort or user attributes, enabling you to estimate the impact of each opportunity and build a product roadmap.
3. Shareable dashboards
You can save all the above analyses as charts and pin them to a dashboard to monitor trends. All dashboards are shareable and there are no limits on the number of dashboards you can create.
The following feature comparison table breaks down the capabilities of Blitzllama and Hotjar across parameters that are important for feedback analysis and collection. This will help you make an informed decision by weighing the importance of each feature in the context of your product research and user feedback needs.
In-App Feedback Collection
Web and Mobile Presence
Both Web and Mobile
Customization & Personalization
Available in Higher Plans
Event-based Survey Triggers
Single Feedback Repository
AI-Powered & Comprehensive
AI-Powered Survey Summaries
Uses GPT for Feedback Categorization
Integration with Analytics Tools
Event Syncing Only
Cohorts and Event Syncing
Higher (Approx 2x of Blitzllama)
Flat Subscription (Unlimited Responses)
In summary, while Hotjar provides a strong suite of features for tracking user behavior on web pages, it falls short in the in-app feedback collection and analysis domain. Blitzllama emerges as a more specialized and cost-effective alternative for product research teams. It offers extensive customization, personalization, and data quality control features, in addition to supporting both mobile and web platforms. Moreover, Blitzllama's AI-powered feedback analytics and its ability to centralize data in a single repository facilitate efficient and data-driven decision-making for product teams.