It helps us a lot in monitoring the brand on social networks, as well as getting to know our target audiences better. It is a very …
We use Brandwatch Analytics as the core technology for our research into conversation around brands and entertainment properties and …
In an educational environment, I teach a Social Media course in which we use Brandwatch to track salient topics of interest to our …
It's used by a single department - social media monitoring team. It solves the issue of monitoring and understanding social media buzz and …
The Brandwatch tool is used to generate consumer insights using the social data for clients, as a service company we provide listening …
We are engaging with Brandwatch on two fronts. First, to inform us globally on our industry while also informing us on various niches. …
Initially a listening tool for our social team to better understand the audiences they could tap into, Brandwatch Consumer Research …
Currently used as the main reporting tool for board and senior leaders on understanding social media commentary and exposure the business …
Brandwatch is the perfect listening tool that gives users the best control over data analysis in a user-friendly and simple way. Compared …
We are using it for our website and social media. The company mainly uses it in our Marketing Department so we can get raw and generic …
We currently use Brandwatch for competitive analysis and market research for new business pitches. It is mainly used by our digital …
We are using it as a social media listening tool to hone in on conversations, overlapping consumer interests, and social performance …
Across our company, it was mostly used in marketing and social care (who was responsible for the brand listening within our organization).
Brandwatch is used by our media and data team at my company. But reports and findings generated through Brandwatch are shared with our …
Brandwatch is being used by myself and our clients' in house community management and analytics team. I use Brandwatch mainly for social …
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- Premium Consulting / Integration Services
Brandwatch, from Cision (acquired February 2021) is an enterprise social intelligence platform that is designed to allow brands to listen and analyze online conversation to extract meaningful insights, inform their business decisions and understand more about the return on their marketing spend.
- Supported: Proprietary listening technology providing quality data coverage
- Supported: The most advanced, customizable charting and analysis functionality available
- Supported: Unlimited users and a range of distrubution, sharing and permissions options
- Supported: Flexible dashboards with over 25 different components
- Supported: 30+ fully-supported languages, including Topics and sentiment extraction
- Supported: Sophisticated demographic and theme analysis
- Supported: Owned Twitter and Facebook channel tools
- Supported: Automated, intelligent and custom alerting features
- Supported: Bulk processing and automation of categorization and tagging
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|Small Businesses (1-50 employees)||9%|
|Mid-Size Companies (51-500 employees)||20%|
|Enterprises (more than 500 employees)||70%|
Companies can't remove reviews or game the system. Here's why
- Improve the customer experience
- The connection via API is very good
- Its flexibility and scalability adapts to all types of organizations
- The analysis and monitoring of influencers
- Sentiment analysis using AI
- Higher level of audience data filtering
- Highly programmable setup allows for deep categorisation of social and online conversation data.
- Useful and clear UI that allows easy access to granular reporting.
- Highly responsive and knowledge support and account management teams.
- Company is clearly committed to evolving their platform for their clients as well as being responsive to their recommendations.
- The UI sometimes struggles with larger categorisation sets but this can be worked around by exporting to Excel and creating your own graphs there.
- Filters textual data
- provides excellent options in terms of dashboards
- very efficient and timely data downloads
- quick response from the support team
- I would like to have larger data downloads per day. Our unit is limited to 50K lines of data per day.
- I would like to see a more comprehensive historical data pull
- Crimson is a pioneer in applying the supervised machine learning algorithms for sentiment classification. Hence the sentiment engine is robust.
- I personally like the topic wheels that show the overarching topics and sub topics in an easy to understand wheel representation.
- I also like the word associations network graph that it provides for top keywords. Very informative and engaging graph.
- Currently the sentiment classifier has a minimum number of mentions that need to be tagged initially for training the tool on the desired classification. But this is tedious when we have lots of sentiment or categories. For ad hoc analysis use, we need a simpler system to see basic sentiment analysis.
- I suggest that the creation and duplication of dashboards are not geared for repeated usage over time. It is not flexible enough to be shared to other users etc.
- Data sources need to be expanded from the current offering.
- It helps to create Consumer Insight report
- It helps to create Influencer Analysis report
- It helps to create Campaign Analysis report and see the performance of the campaign
- Image recognition features
- Speech Analysis features
- Attractive wordcloud
- Media coverage database.
- On-ramping from zero to action.
- More reporting template options.
- More alerting options.
- High Customization
- Huge Data Source
- Access to Historic Data
- Exporting Dashboards
- Automated Exports
- Very detailed in its thematic and keyword based searches.
- The ability to crease multiple levels to predefined filtering allows for cleaner results.
- Too comprehensive means it is more of a reporting tool than an investigations tool.
- The filtering defaults are often misused to predefine keyword filtering... how can we be sure users always use the same keywords.
- Tagging and categorizing.
- Data charting, filtering, and analysis.
- Integration of external data sources on analytics platform.
- Sentiment analysis.
- Social mentions.
- Social influencers.
- Pulling historical information.
- Pulling information evenly across online channels.
- Identifying negative comments vs positive comments.
- Their UI is easy to understand.
- Their data gets updated in real-time.
- The ability to provide detailed, analytical reports is nice in a budding social media landscape.
- It's not all-encompassing. In other words, there aren't a whole lot of insights from our PR hits and how they perform on social.
- Social listening.
- Campaign reporting.
- Manipulation of the data (visually).
- The learning curve is steep.
- Price tag.
- Wasn't able to pull all the metrics our organization needed.
- Clean, beautiful visuals that can be easily incorporated into reports to be used internally and externally.
- Customization-- anywhere from the queries you create to adjusting individual report widget/components this tool is very flexible.
- Excellent Customer Service and support. My Brandwatch rep is always open to hearing from me for questions and often reaches out to me to check in on my status or see if I would like to participate in beta programs.
- Constant innovation. It seems like Brandwatch is constantly updating and adding improvements to their platform--especially with their 2019 acquisition of Crimson Hexagon.
- Query building learning curve. To get the most out of query set up, using the Query Editor is best, but learning the nuances of this process can be hard if you don't consider yourself to be very tech-savvy.
- It would be nice if widget color schemes were adjustable so graphs could be catered to specific report styles. Our company aesthetic doesn't really match with the rainbow-colored widgets created by Brandwatch, so sometimes they stand out in a bad way in our reports.
- I know this is something they are working on, but the current AI classification and learning abilities are limited (as of Oct. 2019). Part of their road-map with their Crimson Hexagon acquisition is to incorporate smarter classification and AI to help filter out irrelevant mentions.
- Sentiment classification is unreliable sometimes depending on the subject matter. If a user is being funny or sarcastic in a mention, the sentiment algorithm gets really tripped up.
- Social listening
- Sentiment Analysis
- Trend Spotting
- Sentiment Analysis could be more accurate
- Easier Interface to use
- More explanation on when boolean terms are not applicable
- Slices and dices data by different keyword sets and visualizes it however you need it
- Doesn't limit the number of queries
- Allows for highly customized dashboards
- Makes it easy to limit access based on user logins
- Very steep learning curve- good luck training casual users on the difference between a query, a rule, a category etc
- Lack of access to FULL historic data is a serious drawback- populating that data takes a minimum of 24 hours and incurs additional costs
- Volume limits mean you may have to build your query to exclude mentions that may be useful in getting the full context of the situation
- Data you can trust
- Fast easy-to-learn UI
- Functionality that translates well across users - I.E. a team member can use it and will see the same result you do.
- Crisis monitoring support
- Unbranded or white-label report development
- SQL support
- Brandwatch is great with bulk changes in mentions, which I believe is also a USP as I haven't seen any tool do that (I have checked out many).
- You can bulk tag, change sentiment, add rules, add categories etc. to mentions.
- From tagging and rules comes good analysis of mentions. Once categorised, you'd be able to understand what are people taking the most about - in a negative or a positive way. Say a telecom company wants to know why people don't like my services - is it the network, or customer service or something else. Do people from a particular city complaint a lot?
- Brandwatch also does a good job at capturing a huge amount of mentions from 90M+ websites. That's 2x or 3x more in some cases than the few leading enterprise listening software.
- It also provides the maximum number of metadata per mention thus giving maximum scope of slicing the data and analysing in different ways.
- I feel Brandwatch needs to add more sources with proper API integrations. The integrations are limited to Instagram, Facebook and Twitter. While Twitter gets great coverage, Facebook and Instagram do not (considering the recent policy changes, coverage has been limited). While it does capture 90M+ other sites which include most of the other social media sites such as Youtube, I feel an integration with such sites can get more analytics around usage data such as video viewing times, view growth on Youtube.
- While they have a lot of insights already, I feel a few word clouds could have been done differently as well, such as word connections. Also, more accurate auto-categorisation of mentions where manual rule adding isn't needed.
- E-commerce review coverage (Amazon etc.) should be included.
- The breadth of the data it captures is impressive, and you are only limited in the tool by your own knowledge of how to use the system. Therefore, if you know how to create smart, tightly structured queries, how to create smart rules to help save manual search and filing, already have a set of keywords to plug in to your query, and know how to use the more advanced chart visualizations beyond the stock ones they provide, you should be in great shape.
- The range of historical data, as well as the ability to access it in detail is a definite plus that puts them above competitors if you're looking for long-term historical trends.
- The visuals are basic, but look nice, and the ability to export most of the graphs and charts is very useful when putting together presentations.
- Depending on your prior knowledge, there could be a steep learning curve. Don't get me wrong, their customer service/account management is fantastic-- they take you through an initial training and are happy to answer any questions you have, but it's hard to articulate what you don't know, just starting out, so there's things I'm only learning how to do after a year of using the tool. I like to think of it as a very power shell/big data source. If you know exactly what data you're looking for and already have the necessary keywords to build a query, you can do great things. If not, it will be an uphill struggle at times.
- Many of its competitors have "quick search" type functions that are great for new business pitches or other situations where you're starting from square 1, while Brandwatch does not in its basic product and offers it as a separate product for additional fee.
- While the visualizations are serviceable, they are quite basic don't allow flexibility, so many times I end up exporting the data and creating my own in other tools.
- Intelligence on identifying sentiment is lacking without your own rules, training it, etc. I spend a fair amount of time re-categorizing mis-filed sentiment on posts.
- Drills down to specifics of what is being discussed on social media
- Very robust set of analytics tools
- Topic wheels are extremely useful for identifying trending topics
- It is a very costly tool
- The pricing packages are not the most intuitive to understand when going through the contract process
- The user interface could be improved to allow for more efficient usage
- Solid visualizations and reporting capabilities
- Shared workspaces to collaborate on social listening reports
- Share of voice studies among brands' competitive sets
- Word clouds and topic waves are often difficult to generate if there isn't enough conversation volume
- Visuals for share of voice comparisons are often hard to interpret
- The measurement variables it can export and show are a great asset. For example, within an export or dashboard I can see follower count and engagement metrics at post-level, which we have not seen another tool do.
- Hashtag tracking on Twitter is very robust and especially helpful when running sweeps and counting entries.
- We love having the option to set what percentage of the Twitter Firehose we want to capture, so we're not limited to the Twitter Decahose.
- Capturing data on Instagram can definitely be improved, since we've found some gaps when tracking hashtags.
- Tracking Instagram is only limited to hashtags, so it would be great if we could also do keyword tracking.
- It is not the easiest tools to help identify conversation themes quickly. It usually takes a little longer to dig through the data/dashboards/widgets to help land on conversation insights or audience interests.
- Boolean queries let you fully customize.
- Multi-language analytics.
- The geography description is very vague.
- Twitter coverage is very strong, which provides for accurate data and flexible measurement capabilities. Data sets include follower count, following count, replies, and retweets which sample data points that are not always available in other platform unless you are authorized as the owner of the channel.
- The entire platform is robust yet flexible. There are advanced Boolean operators that can be used to create complex queries. Then, when ready to analyze the data, the dashboards provide an almost endless way of filtering, categorizing, tagging, drilling down into, slicing, and dicing the data however you need to see it to answer your business problem.
- Customer service has always been timely and interactions are positive. They can usually solve a problem or at least give you a response to let you know they are working on an issue well within 24 hours.
- Instagram data coverage is not very strong. Though there are industry-wide hurdles in tracking data on Instagram, there are competitors that have proven more accurate than Brandwatch.
- Many larger, more broad queries return a lot of junk or spam posts. Customer service can help with filtering these out with common "NOT" operator phrases. However, some competitors do a better job on the back end to make sure you never see as much as the spam to begin with.
- Monthly data limits are a con if your work requires a lot of ad hoc projects and it's hard to project the monthly volume you will need.
- Clearly presenting the most important metrics and information
- Capabilities of slicing the data up however you choose
- I like the ability to easily change the date range
- I would like to see a single metric for sentiment (e.g., net sentiment)