Ent-Social-Intelligence-Report.Pdf

Contents

1.0.0 EXECUTIVE SUMMARY ...... 3 2.0.0 INTRODUCTION ...... 4 2.1. Social Intelligence for the Social Business ...... 5 2.2. Risks of an “All-in-One” Solution ...... 5 3.0.0 THE SOCIAL INTELLIGENCE STACK ...... 7 3.1.0 Brandwatch Social Intelligence Model ...... 8 3.2.0 Social Listening ...... 9 3.3.0 Data Management ...... 10 3.3.1 Data Management: Automation ...... 10

3.3.2 Data Management: Workflow ...... 10

3.3.3 Data Management: Dashboards ...... 11

3.4.0 Advanced Analytics ...... 11 3.4.1 Advanced Analytics: Advanced Boolean ...... 12

3.4.2 Advanced Analytics: NLP Topic Extraction ...... 13

3.4.3 Advanced Analytics: Pattern Detection ...... 15

3.4.4 Advanced Analytics: Audience Intelligence ...... 16

3.4.5 Advanced Analytics: Influence ...... 17

3.5.0 Distribution ...... 17 3.5.1 Distribution: Custom Dashboards ...... 17

3.5.2 Distribution: Reporting ...... 18

3.5.3 Distribution: Command Centers ...... 19

3.5.4 Distribution: Alerts and Notifications ...... 19

3.5.5 Distribution: API ...... 20

3.5.6 Distribution: Ecosystem ...... 20

3.6.0 Innovation ...... 24 4.0.0 CONCLUSION ...... 26 5.0.0 THE BRANDWATCH SOLUTION ...... 27

1.0.0 Executive Summary

Social data is ubiquitous. With the number of brands, markets and departments in large organizations, it’s clear that social data will continue to increase in importance to a range of divisions throughout the enterprise, with each team requiring unique applications for social data. Some of these needs will be met by legacy systems, while others will require complementary or completely new systems altogether.

Vendors like Salesforce, Adobe and Oracle have spent billions of dollars acquiring technologies that meet the social data needs of every department and use case. Slowed by the task of integrating these disparate technologies, they have inevitably fallen behind the curve as new use cases develop, new social networks arrive and online behaviors shift.

Adopting a similar strategy under a lesser budget, smaller vendors like Sprinklr, looking to extend their offerings horizontally, have faced the same obstacles: limited or no integration of disparate technologies behind the UI, disjointed user experience and reliability, and a constant tension between the depth and breadth of their output given expanding use cases, social networks and data.

Citing these historical examples, leading industry analysts agree that the range of use cases social data can support will inevitably outpace the abilities of a single vendor. Rather, an ecosystem of inter-communicating platforms will be required to provide complex organizations with both the breadth and depth it needs to succeed in social globally.

As the volume, variety and velocity of social data continue to increase, interpreting social data will remain a core part of this ecosystem. While brands’ global social footprint expands at or ahead of this rate, the ability to efficiently leverage social data at scale is dependent on utilizing a social intelligence stack: comprehensive listening, data management, advanced analytics and distribution of insights.

2.0.0 Introduction

A social business describes an organization that leverages the proliferation and capabilities of online communication to inform, optimize and facilitate operations throughout the enterprise.

Over the past decade, social media’s role has matured from a narrow focus into a core dependency that empowers divisions across the entire business. Indeed, executives cite more than 13 distinct divisions with staff dedicated to using social media to promote their team’s operations.1

Fig 9: At Least 13 Business Units Have Dedicated Social Media Staff

Q. In which of the following departments are there dedicated people (can be less than one FTE) executing social? (Q4 1012)

Marketing 73%

Corporate/PR 66%

Customer Support 40%

Digital 37%

Social Media 35%

HR 29%

Product Department/R&D 16%

Advertising 16%

Customer/User Experience 15%

IT 14%

Executive 11%

Legal 9%

Market Research 8%

1 Altimeter. The State of Social Business 2013: The Maturing of Social Media into Social Business

2.1. SOCIAL INTELLIGENCE FOR THE SOCIAL BUSINESS One of the defining characteristics of a social business is social intelligence. Extending well beyond listening, which deals primarily with identifying conversations, social intelligence allows businesses to segment, analyze, understand and distribute social insights at scale and in real-time.

"Social intelligence involves capturing, managing, and analyzing social data to identify and apply insights to business goals. In the age of the customer, companies must prepare fast, data-driven strategies to exceed their customers' demands. As a result, more and more businesses turn to social intelligence”

– Allison Smith, Customer Insights Analyst at Forrester Research

2.2. RISKS OF AN “ALL-IN-ONE” SOLUTION “More than two-thirds of avid social marketers believe it’s more effective for them to buy all their social tools from a single vendor than to buy social point solutions from several different vendors. But they couldn’t be more wrong.”

– Forrester Wave™ Social Relationship Platforms, Q2 2015

Given the range of functionality required to manage social data at scale and the distinct needs of a variety of departments, it is becoming clear to industry experts that any all-in- one suite will involve significant compromises.

“There’s little value in unified social suites. Both large and small vendors are racing to cover all four social technology categories. And sure, listening data provides useful insight to the other social tools. But we see little value in connecting your community platform to the technology that manages your Facebook page or in connecting either to a social ad-buying tool. And the unified suites are rarely best in class for individual technology categories.

Witness salesforce.com: While it credibly offers marketers three of the four social tools, its Buddy Media social relationship platform is merely middle-of-the pack, and its Radian6 social listening platform has lost its market-leading position since being acquired.”

– Allison Smith, Customer Insights Analyst at Forrester Research

Forrester reports that clients relying on all-in-one solutions run the risk of handcuffing themselves to technologies that quickly grow out-of-date as a lack of focus and specialization hinders innovation and progress. This implies that there could be a significant risk for clients to underperform in critical business areas when depending on these types of broad tools.

A quick look at the social media monitoring landscape presents evidence for Forrester’s observation. After Salesforce and Oracle acquired market leaders Radian6 and Collective Intellect respectively, their company size and diluted focus impeded their development against a backdrop of nimble point solutions. An inevitably similar principle applies to the acquisition of vendors such as Vocus, Visible Technologies, UberVU and Dachis Group.

“The complexity of the digital marketing stack can only sustain a limited number of solutions/platforms, but no single vendor is going to provide such a compelling end-to-end solution that it's unnecessary to use any others.”

– Andrew Jones, formerly Analyst at Altimeter Group, now at VentureBeat

Many smaller companies, promising the ultimate holistic social platform, have constructed their suite by targeting and acquiring affordable technologies. Not only do these companies face the same integration and innovation challenges as Radian6 and Collective Intellect, but they are additionally disadvantaged by a suite comprised of sub-standard components.

Acquisitions are often selected on the basis of what’s available. This is seldom a market leader, and will often represent a struggling vendor seeking a buyer. Further complicating the process is that there is no unified technology for building marketing platforms, meaning different languages and architectures can prove extremely difficult when it comes to integrating the platforms into a single offering.

It’s also worth noting that the development time spent sewing together disparate technologies into a single patchwork can be significant, and as more engineering resource becomes dedicated to integration, product innovation and new feature development can quickly get sidelined.

In attempting to offer a little bit of everything without completely doing one thing, these platforms are inevitably a mile wide and an inch deep.

3.0.0 The Social Intelligence Stack

The Brandwatch solution goes beyond social listening, providing a social intelligence stack to inform decisions, improve processes and create new opportunities. With the largest engineering team dedicated to developing social intelligence technologies in the world and an extensive group of PhDs in our research and development team, the Brandwatch platform offers a number of important and distinct advantages.

In addition to leading automated sentiment analysis and renowned Natural Language Processing techniques, Brandwatch provides a range of unique algorithms and analytics tools to decipher the signal from the noise. Many of these technologies are new to the industry, ensuring that Brandwatch clients remain at the cutting-edge of social intelligence. The following section covers many of the detailed processes and capabilities that define a social intelligence platform.

3.1.0 BRANDWATCH SOCIAL INTELLIGENCE MODEL Before diving into the individual aspects and applications of social intelligence, it is essential to understand the structure and layers of technology involved in the social intelligence stack.

DEPARTMENTS

SOCIAL BUSINESS USE CASES

DISTRIBUTION

API REPORTING COMMAND CENTER DASHBOARDS NOTIFICATIONS ECOSYSTEM

ADVANCED ANALYTICS IMAGE ADVANCED BOOLEAN TOPIC AUDIENCE SENTIMENT SIGNALS INNOVATION

MANAGEMENT

WORKFLOW AUTOMATION CLASSIFICATION

SOCIAL INTELLIGENCE SOCIAL LISTENING BASIC BOOLEAN COVERAGE SOCIAL DATA ARCHIVE

Social listening is the foundation of social intelligence. The breadth of online crawlers, backlog of historical data and accuracy of search queries determine the quality of data collected.

In the data management stage, data is classified and segmented into organized and manageable packages of specific conversations. For the social data points in each package, advanced analytics identifies key attributes of that conversation. Lastly, the distribution phase deals with how that information is then translated into easily digestible insights, triaged to the appropriate departments or incorporated into a larger set of essential business data.

3.2.0 SOCIAL LISTENING The social listening stage defines the process of collecting social media conversations. That process may include pulling posts from the public Twitter API, buying data from vendors such as Datasift or using an in-house network of crawlers that collect and store data. The process determines the quality of the data and affects everything that follows in its wake: it is at the core of any social solution.

Yet not all social listening technologies are created equal. Many platforms that offer basic listening and analytics, such as Hootsuite, will still partner with Brandwatch to provide social intelligence capabilities to enterprise clients.

Expert social listening provides:

• Clean, spam-free data collected from millions of online sources • Instant, real-time data • A constantly increasing volume, velocity, and variety of social data • Comprehensive coverage with full metadata, sentiment and topics across multiple languages • Historical data to review, compare and spot important industry trends • Highly isolated searches to pinpoint specific conversations

It can prove difficult to dissect capability in this area, with vendors each claiming seemingly random numbers of ‘sources’ from which they provide data for. This ranges from ’25 social networks covered’ to ‘data crawled from over 500m sources’. With no universal system of measurement, it’s important to establish what is meant by ‘source’, and what is meant by ‘coverage’.

For Brandwatch, we determine a source as a single site from which we pull data from. Twitter, Facebook and BBC News would each count as one. Other vendors may count these in another way, by counting the individual authors, tweets or news articles as separate entities, for example. Brandwatch provides coverage for around 80m of these sources, as tallied by the ‘single source’ methodology.

Furthermore, there are some sites and networks for which it is impossible to secure complete coverage of. Sites like Instagram, YouTube, Google+, Pinterest, LinkedIn, The New York Times and The Sun all deliberately limit the volume of data that can be gathered by listening technologies. Brandwatch is engineered to maximize the quality and breadth of data taken from these types of sources, but we are frank in disclosing the limitations of data drawn from them.

In such a complex and unaligned space, transparency forms the backbone of any vendor seeking to form meaningful, deep relationships with users based on trust. For those in the process of selecting a listening technology, uncovering the real meaning behind coverage claims – and by extension, the quality of listening functionality - is imperative to choosing the right tools.

3.3.0 DATA MANAGEMENT Listening is crucial, but is only the first step in social intelligence. After gathering that data, the management of it becomes the next important process.

Data management deals with the way in which social data is segmented and routed in an efficient manner. This critical stage is how small teams can prepare extremely large data sets for an array of departments to undergo sophisticated analysis.

3.3.1 Data Management: Automation Automated ‘Rules’ allow users to set up custom rules that automatically tag specific conversations within a dataset. Brands will often apply an automated Rule to classify conversations relating to a particular product characteristic or a specific campaign, or to flag different motivations such as purchase intent or complaints.

Automated rules are critical for data management at scale and save an immense amount of analyst hours each month. Some Brandwatch customers create and make use of thousands of these customized rules. Since this data management works in real-time, any downstream channel for this data will have an immediate view of the organized data.

In addition, the automation features (Rules) support custom sentiment classifiers that supplement or replace the automated sentiment engine logic based on specific client needs. This grants users the ability to apply product or industry-specific terms to sentiment classifiers. This is especially useful for ambiguous terms like 'sick' in the context of youth slang versus healthcare products, or when PR-related hashtags emerge and reflect a negative impact to brand reputation, as in the case of Apple’s #bendgate.

3.3.2 Data Management: Workflow As well as tagging, the Brandwatch data management system also automates the routing and prioritization of posts. Using Rules, the system can automatically route a post to an individual user depending on the post’s content, sentiment or for numerous other criteria. Similar filters also allow the priority level of the post to be automatically assigned in real time – a powerful way to manage social inboxes.

3.3.3 Data Management: Dashboards In order for social media data to inform business decisions, an analytics platform must provide flexible ways to dissect the information into actionable insights.

With more than 24 dashboard components, Brandwatch Analytics allows users to segment and view data in more ways than any other platform. The Chart component alone can display 13 aspects of the data across 37 criteria, meaning that a single component can display the same dataset in over 17,000 unique ways.

Using the extensive filtering options available on our dashboards, users can also narrow in on or compare specific subgroups based on a comprehensive list of criteria. Some of Brandwatch’s industry-leading 54 distinct filters include:

• Date and time: from monthly to minute intervals • Location: from continent to city • Page type: news, blogs, forums, Twitter, Facebook, review etc. • Twitter statistics: retweets, influence metrics, impressions etc • Facebook statistics: media type, likes, comments • Sentiment: positive, neutral, negative • Site visitors and domain authority • Gender, profession, interests and other psychographics

Furthermore, all of these views can be shared within the platform or directly exported as images or structured datasets. Such customizable features within Brandwatch Analytics afford an unprecedented level of analysis, designed to be as flexible as possible to best serve the specific needs of the brand or team dissecting the data.

3.4.0 ADVANCED ANALYTICS A critical but often invisible layer of the social intelligence stack is the advanced analytics. Brandwatch has a team of more than ten PhDs specializing in subjects from Linguistics to Astrophysics. Their role at Brandwatch is to work with developers to create and implement analytics and algorithms that can be automated to find meaning in vast data sets.

3.4.1 Advanced Analytics: Advanced Boolean

“The problem of how to distinguish good information from bad, that problem has been with us since we started communicating”

– Sir Tim Berners-Lee, World Wide Web Consortium

As is the case with all analytics, valuable insights begin with the data. The unique challenge of conversation analytics is not in finding every relevant mention but in finding only relevant mentions.

For a term like Bounty, analytics platforms must be capable of deciphering if the conversation is about the name of a coconut chocolate bar, a global brand of kitchen roll, the reward given for capturing criminals or a 19th century maritime mutiny. If an analytics tool cannot accurately decipher these discussions, the data will be too muddy to extract any meaningful insights. The same is true of brands such as Sprint, Subway, Delta, Apple, Next and Three – multiple nuanced meanings require a sophisticated approach to distinguish relevant conversations from the noise.

Brandwatch’s advanced search capabilities, which are based on Boolean language operators, allow the user to develop Queries that pinpoint a specific subset of conversation. While lightweight listening tools offer basic keyword search operators like AND, NOT and OR, these simple searches are hugely flawed for any serious analysis.

Brandwatch offers 22 Boolean operators: far more than most other vendors in the industry. Additionally, Brandwatch Queries can be refined by: location, site, exclusion terms, authors and even a word’s proximity to another. Allowing queries of over 4,000 characters, users can craft highly tailored searches that take into account the many variations of colloquial expression.

Such granularity ensures that the data is clean, precise and capable of driving valuable insights.

3.4.2 Advanced Analytics: NLP Topic Extraction An effective topic analysis allows businesses to glean a quick overview of the popular topics within any conversation. Basic listening tools calculate using a word count showing the most frequently used, single words in the cloud. Some don’t exclude words such as “is,” “to,” or “of” creating excessive noise in the results. These topic clouds are often misleading and uninformative.

NLP Phrase extracted topics tell the story

Static topic clouds are next to useless, which is why Brandwatch’s Topics functionality is built with a typical degree of flexibility in mind.

1. Zoom-in capabilities: view topic clouds within topic clouds by clicking into key phrases 2. The data behind the cloud: like with all components, users can click through to discover the specific conversations behind each topic

3. Category clouds: allows user-created categories and tags to also be displayed, either instead of or as well as the algorithm-generated topics 4. NLP processing: extraction of noun-phrases, providing context around the topic rather than single word entries 5. Sentiment spectrum: shaded coloring of terms indicates the relative sentiment strength for each topic displayed 6. Table view: presenting, dissecting and exporting the metrics behind the topic cloud visuals 7. Multiple queries: combine and compare different brands, products and themes in single or multiple clouds in t he same dashboard 8. Trends: display the topic cloud by volume or burst, highlighting either the most talked about terms, or the terms growing at the fastest rate. 9. Topic comparison: view topic clouds across demographic variables including gender, interest, account type and profession

These processes reflect the distinction between a basic social listening tool and an expert social intelligence platform. There is a significant difference in the business applications of a feature that simply presents the data and one that allows users to dive deeper into and understand the data.

3.4.3 Advanced Analytics: Pattern Detection Signals is a pattern-detecting analytics engine using proprietary algorithms to understand new, potentially important, activity taking place around a brand in social media and proactively update users with an overview of the situation via email.

Released in 2015, Signals made the corporate communications team at a American national retailer aware of a very tragic on-premise shooting 12 minutes ahead of any other channel, including local news outlets and the in-store security team. This valuable time enabled them to alert emergency response units, raise the security level at hundreds of stores and initiate their response process so they were ahead of the crisis.

Signals will inform any team member including the C-Suite, PR and brand managers who do not have time to work in the analytics platform regularly but need to have a finger on the pulse of what is happening around the brand at any given time.

This revolutionary product is delivering high-level analysis and insights beyond data scientists. It is helping more people in the business become aware of emerging trends in data, detecting changes that may have been found more slowly - or even missed altogether - by an analyst.

3.4.4 Advanced Analytics: Audience Intelligence To further deepen its capabilities in audience intelligence, in 2014 Brandwatch acquired the award-winning company PeerIndex, inheriting the single largest independent database of Twitter authors in the world: an index of over 300 million users. By using advanced machine learning algorithms on tweets and the social graph, Brandwatch is able to classify these users by geography, demographics, network influence and topics of interest.

Research we undertook in 2013 revealed that just 3.6% of tweets mention a brand. By building a product that supports audience-led research, brands can discover the other things important to different consumer groups – going far beyond the ‘what did they say about my brand’ approach.

3.4.5 Advanced Analytics: Influence The Brandwatch platform currently includes a proprietary Impact Score, a unique influence metric aimed at comparing social influence across multiple publication platforms – meaning that the influence of a tweet can be compared with a blog post or news article, for example.

Influence features in Brandwatch are, as ever, designed with customization in mind. Rather than pushing a single framework for identifying influential authors, by providing:

• aggregated metrics (Kred, MozRank, Impact etc.) • native platform metrics (follower counts, traffic data, forum posts etc.) • useful filtering (gender, location, volume of relevant mentions etc.)

Users can select the data that’s relevant for finding influencers most relevant to their priorities.

3.5.0 DISTRIBUTION The distribution stage ensures that insights are delivered to the appropriate teams, in the desired format, and on the preferred system. Fast and intelligent distribution across the business is critical for enabling organizations to quickly react to threats and opportunities online.

Brandwatch provides customized data delivery to fit the needs of any user or department. Additionally, based on advanced algorithms, the platform itself can identify and recommend what information may be important and share it automatically, providing analysts and PR professionals with automated updates.

3.5.1 Distribution: Custom Dashboards The unique flexibility of Brandwatch dashboards has allows users to design the optimal dashboard layout tailored for each team and with specific use-cases in mind.

Brandwatch’s permissions system, developed with direct feedback from customer input, allows our customers to maintain a small team to effectively manage the access rights of other users in the business. The latest iteration ensures that users only see what they need to and that data is only changed by authorized personnel. Such multi-level access controls not only safeguard enterprises from security breaches, but also prevents untrained users from creating costly mistakes.

Data is additionally protected by Brandwatch’s optional Single Sign-On (SSO) offering with Security Assertion Markup Language (SAML), which has been iRisk approved.

3.5.2 Distribution: Reporting

Automated Reports

Brandwatch’s Automated Reporting enables brands to save valuable analyst hours through the scheduled distribution of automatically generated insights reports. This adds a powerful option for users who do not have time to access dashboards from the platform directly but rely on regular updates of social statistics.

Analyst Reports

As well as Automated Reports, Brandwatch professional services teams across North America and Europe support enterprises with analysis and insights in any system supported languages. Analyst reports cover anything from crisis reporting to analyses on the correlation between social data and focus groups.

3.5.3 Distribution: Command Centers Brandwatch’s social media command center product, Vizia, leads the market in data visualization for brand monitoring and crisis response command centers. Vizia is a real- time system that is powered by Brandwatch Analytics, but also allows users to pull in and display information from outside data sources. Vizia supports multiple screen implementations, can be tailored to show relevant visualizations to different teams, and is seamlessly managed via desktop, tablet or mobile.

3.5.4 Distribution: Alerts and Notifications Facilitating access to social data is crucial for the social business. At no extra cost, Brandwatch enables users to create Alerts and notifications for the employees of its customers, even if they don’t have or need dashboard access.

Some Brandwatch users have set up have more than 300 sophisticated Alerts operating in Brandwatch. These alerts can be based on content by scanning for mentions of specific topics, or thresholds by identifying spikes in the volume of anything from specific product conversation or general brand sentiment.

Additionally, Signals notifications - powered by the aforementioned pattern-matching engine - also represent a valuable resource for alerting. Organizations are able to designate who receives specific Signals. Users will be notified of the “unknown knowns”: shifts from the norm for brand data around elements like volume, channel, hashtag use, influencers and sentiment.

3.5.5 Distribution: API “Some vendors are trying to push the curve outward by offering better APIs for third-party point solutions, becoming more open platforms. This often gives you many more choices for more specialized capabilities — you’re not restricted to just what’s hardwired into the suite. Good APIs are one of the primary reasons that integrations between different marketing technologies are getting easier.

More importantly, an individual marketing organization can expand its frontier by crafting a clear marketing technology strategy and applying good marketing technology governance. This includes establishing a well-defined process for deciding which point solutions — and which conglomerate solutions — to implement and how to handle the integration points between them.”

– Scott Brinker, chair at #MarTech conference & author of Chief Marketing Technologist

Social data does not operate in a silo; enterprise clients, with a variety of data sources, often need to incorporate social data into outside applications. Therefore, Brandwatch offers clients a fully supported, comprehensive and reliable API to easily distribute social data wherever needed. Brandwatch’s API delivers data from more than 80 million sources and is one of the very few Twitter-authorized APIs allowed to pass full Twitter content to third-party systems.

3.5.6 Distribution: Ecosystem “Suites are being replaced by ecosystems, or technology matrices, or whatever else doesn't imply a single entity providing everything. You could say that the reason for this is that interoperability is better than ever – one application can live with another from a different vendor more easily than before.“

– Paul Greenberg, President of The 56 Group and author of CRM at the Speed of Light

Though the needs and complexity of every organization is different, one thing that remains true is that they rely on a broad set of technologies to achieve their objectives. No single vendor can address every use case to a satisfactory level, especially with the high

demands of function depth and innovation. This means that for organizations to evolve as a social business, they must rely on critical data and insights to pass between systems and platforms throughout the enterprise, and not be limited to any siloed application.

“Every year, new disruptive innovations arise across our connected, digital world, like from star foundries, birthing new expectations and potential competitive advantages.

It’s been impossible for any one software package to keep up with all of these growing constellations. So you have many different software vendors addressing different parts of this universe — i.e., different stations on Gartner’s transit map.

Now, any one marketing organization certainly doesn’t need to cover the entire universe. But you do have to decide which parts are essential to the expectations of your customers and which parts are going to be key to your differentiation strategy.

This is the heart of marketing technology strategy.

You pick the marketing technologies that best help you achieve your marketing strategy. You seek to minimize cost — integration costs included — but you also seek to maximize impact. If you only optimize the cost side of the equation, you’re dismissing the purpose of marketing in the first place.

And a few choice point solutions will likely be a part of any good, high-impact strategy.“

– Scott Brinker, chair at #MarTech conference & author of Chief Marketing Technologist

Brandwatch’s partner ecosystem - and “best-of-breed” solutions in general - allow brands to choose the best tool for the job without sacrificing intercommunication between platforms, thanks to several partner integrations and an easily adaptable API. Very simply, those organizations that value maximized results over simplistic setups turn to solutions that are optimized for the use case at hand. For example, brands should have the foresight to prepare for a fast-paced and interconnected future, asking themselves the right questions:

• Can marketing capture customer preferences via social intelligence and instantly surface them in a content marketing system to inform the entire campaign workflow, from creative brief authoring to asset creation to channel delivery?

• Can product management get social intelligence data delivered into their project management systems so they can use audience interests to inform and weigh project priorities?

• Can market research identify customers apart from other audience sets by cross- referencing social audiences with the brand’s CRM database to compare how customer perceptions might differ from non-customers?

Crafting a customized, multi-vendor workflow is how forward-thinking organizations facilitate superior business performance, and the Brandwatch API is an example of how Brandwatch structurally supports connectivity and future operations across the broader infrastructure.

Additionally, Brandwatch partners with industry-leading technology vendors such as Percolate, Spredfast and Hootsuite, and offers seamless out-of-the-box integrations with their platforms. More than 2,000 top brands collectively choose these Brandwatch partners to be their preferred social relationship management platform of choice, selected for their outstanding proficiency in content marketing, social engagement, and enterprise-wide adoption respectively.

The implementations can include the ability to monitor and filter conversations from within the engagement platform in real-time, leverage native engagement and workflow functionality with Brandwatch search results, and even utilize the partner’s publishing capabilities from within the Brandwatch dashboard itself. Brandwatch also teams up with leading text analytics firms such as Clarabridge and Converseon to allow brands to aggregate data from both online and offline sources and construct a holistic view of their customers. Given our commitment to an open ecosystem for the enterprise, Brandwatch continues to innovate on its highly flexible API so most any system can build upon a foundation of social intelligence, as well as heavily invest in creating turnkey connection points with the best platforms in the market.

“Marketers who buy point solutions are happier than those who buy social suites” revealing that, on average, clients of point solutions in the Social Relationship Platform ecosystem rate their satisfaction at 4.5/5, compared to clients of social suites, rating just 4.0 out of 5.”

– Forrester Wave™ Social Relationship Platforms, Q2 2015

Just 64% of customers of social suites felt the functionality meets what they were promised (compared to 92% for point solutions).

3.6.0 INNOVATION Remaining at the vanguard of social intelligence requires a constant focus and intelligent strategy toward innovation. Brandwatch’s aim is to both revamp existing functionality, building upon our firm stance as the experts in social intelligence, and to develop or incorporate new technologies, broadening our offering when appropriate.

Our strategy is reinforced by the strong community of clients we have coalesced. On G2 Crowd, the world’s largest enterprise technology review site, validated customers rated Brandwatch’s vision at the highest level – significantly higher than any other vendor in our space. Brandwatch users agree that a focused, best-in-class approach is a stronger long- term plan than opting for an all-in-one suite.

Source: Brandwatch vs ‘all-in-one’ solutions on G2 Crowd

“Social suites rarely offer best-in-class tools. We’ve yet to see any end-to-end social suite maintain leadership across the social technology value chain. For instance, Salesforce offers a social listening platform, a social relationship platform, and a social advertising platform — but none are categorized as Leaders in our most recent Forrester Waves, and both the listening and relationship tools have lost significant ground in the past few years.16 That’s why, in this evaluation, we give credit to vendors who help marketers use their SRPs alongside best-in-class tools from other vendors rather than trying to build their own end-to-end solutions.”

– Forrester Wave™ Social Relationship Platforms, Q2 2015

4.0.0 Conclusion

As the volume and value of social data continue to increase, the capabilities of social solutions are expanding both horizontally and vertically. Leading industry figures, citing market-validated examples, acknowledge that the all-in-one tool spreads itself too thin and cannot adequately keep pace with the capabilities of more focused platforms in such a rapidly expanding space. Businesses seeking an optimal social solution are best served by selecting specialized leaders with seamless data integration.

It’s about building a marketing technology ecosystem that suits the needs of your organization. That may well include suites and point solutions, but must be created on the principle of selecting the right tolls for the right jobs, and investing in technology flexible enough to match the unique requirements of your marketing operation.

5.0.0 The Brandwatch Solution

This document was created to acknowledge and address the ongoing debate concerning single-platform versus multi-platform solutions for businesses seeking to take advantage of social data. We firmly believe that our approach to the enablement of social business is the most effective, and it’s only with flexibility, relevance and customization that technology will meet the needs of unique and evolving enterprise requirements.

Indeed, Brandwatch has evolved far beyond the nascent social listening capabilities and is a social intelligence platform that is constantly pushing the boundaries of social media applications. Our devotion to smart and strategic innovation, our focus on flexible and holistic social intelligence, and the current value that Brandwatch offers organizations stand testament to our perpetual evolution as the leader in social intelligence.

To understand more about how Brandwatch can support your organization’s social intelligence initiatives, book a hassle-free meeting with one of our experts visit: brandwatch.com/demo

Brandwatch. Now You Know.