Three Key Strengths And Weaknesses Of Sprinklr Social Listening
Sprinklr is a unified customer experience management platform, offering a range of capabilities like marketing/advertising, customer service, and social listening. LTIMindtree has worked with Sprinklr to enable social listening for key customers, during which, we have gained a thorough understanding of its strengths and weaknesses. We attempt to provide an analysis in this blog.
Sprinklr’s offerings span across every step of the customer journey, naturally making it a good fit for enterprises that want the full benefit of a social suite.
Sprinklr’s offerings across the customer journey
Here’s a quick overview of the suite of offerings by Sprinklr:
Amongst these capabilities, social listening is a key offering, making Sprinklr one of the best vendors in this space. Sprinklr is a leader in the Forrester wave: Social suites Q3 2021 with the highest score for social listening capabilities.
Key Strengths of Sprinklr
- Integrated Social Suite
Customer journey programs are generally vastly multi-faceted. To ensure optimal experiences at each point of the journey, companies should be equipped with a wide set of capabilities.
A few examples of such capabilities would be to create and distribute content, reach out to customers in a meaningful manner on social channels through campaigns/advertisements/promoted posts, listen to what consumers are saying about the company’s brand, products/services on social networks, review sites, respond promptly/meaningfully when they reach out to the brand, and analyze data.
Multiple tools offer these capabilities and specialize in them, but in most cases, they deal with a siloed set of functionalities. Companies have the option to use multiple overlapping tools to listen, respond, promote, and more – but that may not be the most efficient option.
Sprinklr has an entire suite of social products that are deeply integrated into each other and have considerable breadth to the capabilities offered. The advantages are as follows:
- A single unified experience assures no data importing or exporting, no switching screens.
- Overcoming the silos that exist when individual teams, departments, and their agencies use disparate tools to accommodate their needs. Example: Teams can’t work from the same shared calendar, work from the same project task lists, share notes about incoming messages from customers, or use joint reporting capabilities.
Sprinklr becomes a naturally good fit for enterprises that are looking to gain the advantages of an integrated social suite.
- Pervasive use of AI/Machine Learning
Sprinklr uses AI/Machine Learning across its platform to power multiple capabilities/functionalities. This brings in higher efficiencies, automation, and precision.
A few examples of capabilities powered by AI:
- Sentiment classifications for social mentions: ‘Mentions’ is a cover term for any user post on social media. This could be a tweet, an Instagram post, a Linkedin post, and so on. Sprinklr provides a classification of the sentiments associated with mentions as positive, neutral, or negative, by using machine learning models. This feature is used to solve critical business problems like facilitating identification of the issues/problems consumers have with a product/service, providing a summarized view of public perception of a brand/ campaign/general issue, and the likes. Sentiments work across different languages as well, providing a global range to the applicability to the feature.
- Smart alerts that flag anomalies in the data: one of the most valuable use cases of social listening for businesses is to get alerted in a timely fashion in case of any noteworthy social media trends. Examples include:
- People’s conversations about the company’s brand or competitor brands seeing a lesser/higher number of mentions than normal – This could indicate activity by respective organizations or waning interest, either of which would be useful to note.
- People talking about the company’s brand/products/campaigns negatively or positively – the brand should take prompt action to address the concerns or capitalize to make gains with respect to sales, additional brand visibility, etc.
- Sprinklr’s smart alerts capture any deviation (from the normal) in trends of data points like sentiment, number of mentions, and audience data points like age, location, and the likes using machine learning. Alerts are sent by email, SMS, and other channels to concerned folks for their immediate attention
- Smart Insights that auto-identify contributing drivers to peaks/troughs in data: a common next-step to finding a peak/trough in data (examples: higher number of mentions of a specific term on a day/month, highly positive/negative mentions about a brand, etc) is to find the cause or contributing factors to the peak/trough. Sprinklr makes this process seamless by having its smart insights feature directly provide the major contributing factors. Example below:
- Extensive Data processing, Analytics capabilities
Sprinklr offers strong analytics capabilities, providing a variety of ways through which data can be represented. Extensive customizations as well as configurations can be made to dashboards and widgets.
Sprinklr also allows drill-down on multiple levels into data, allowing users to slice and dice data in any way they desire.
Key Weaknesses of Sprinklr
- Restrictions on capturing ‘mentions’ across some social channels, the capture of personal information
Sprinklr has restrictions on capturing mentions from certain social networks. The primary cause for this is that social networks do not provide mentions to Sprinklr.
Our suggested alternative tools – None.
Most social listening platforms rely on the same data sources as the foundation of their platforms.
According to the Forrester Social Listening platforms overview report from 2018 – Sprinklr scores second highest for its coverage of data sources. Hence, we do not have suggestions for other competitors who could address this weakness.
- Accuracy of sentiment classifications
Sprinklr’s classification of sentiments of posts/comments into positive, negative, and neutral is one of its key features and provides a ton of business value.
However, its accuracy does fall short in certain cases:
- Certain languages: Sprinklr claims an accuracy of 80%+ for its sentiment classifications for languages like English, German, French, Spanish, and 22 others. For less-commonly used languages like Dutch, Urdu, Marathi, and Ukranian, Sprinklr claims an accuracy of 60 – 80%. We have also empirically observed that Sprinklr fairs poorly with Asian languages like Chinese, Japanese, etc.
Our suggestion is to use Linkfluence for Asian languages. This works across multiple regional social networks in APAC like Weibo, WeChat, Zhihu, and Xiaohongshu, including e-commerce channels and travel review sites as well.
It is reported to have a higher level of sentiment classification accuracy for Chinese, Korean, Japanese, etc.
Highly ‘Human’ interactions: Consistent incorrect classifications have been noticed for the following kinds of mentions/comments:
- Sarcasm
- Idioms
- Jargons
- Slangs
Other limitations:
- Difficult navigation/user experience: Sprinklr’s UX has been a noted pain point by customers over many years. While their references note that the UI has indeed improved over the years, it leaves much to be desired in terms of loading times for dashboards/widgets, easy to use interfaces, and the likes.
- Poor visual listening capabilities: visual listening is social listening for images – in different forms like identification of text in images, common images (read brands), as well as identification of images related to textual keywords. The issue with this feature is that incorrect images appear for the keywords entered, apart from the difficulty in moderating the relevance of images that come up.
We suggest that Netbase Quid and Linkfluence be used to achieve better results for visual listening. Both of these vendors are designated by Forrester to have advanced visual listening capabilities.
Our suggestion if a tool/competitor with better UI is desired would be to use Brandwatch or Talkwalker.
Conclusion:
While Sprinklr does fall short in some capacities (especially user experience), it is a well-rounded social listening tool that organizations would derive varied benefits from. We would strongly suggest the tool to any organization which is looking to reap gains from the latest social listening capabilities.
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