With over 300 million social media users in the US alone, the importance of understanding and engaging with audiences on social media cannot be overstated. Two critical practices that aid in this understanding are social listening and social monitoring. While they often seem interchangeable, these terms represent different, albeit interconnected, processes in the world of social media analytics.

Social Monitoring: The Immediate Picture

Think of social monitoring as your brand's radar, scanning the vast expanse of social media to detect mentions of your brand, products, or any specific keywords. It is the process of tracking and responding to individual messages and mentions. The primary purpose? Immediate action. If a customer has a query or complaint, social monitoring allows you to address it promptly.

In essence, monitoring is the act of keeping a finger on the pulse, gauging real-time conversations, and reacting to them.

Social Monitoring Examples in Action

To better grasp the efficacy of social monitoring, let’s explore a few real-world scenarios:

Immediate Customer Service: A boutique hotel chain observes a traveler's tweet about a less- than-perfect room service experience. They immediately respond, offering a complimentary meal, turning a potential criticism into a customer satisfaction highlight.

Brand Protection: Upon launching a new ad campaign, a tech company detects misleading information being spread on Facebook. Through vigilant social monitoring, they quickly correct the narrative, ensuring that their brand message remains consistent and trustworthy.

Amplifying Positive Feedback: An eco-friendly brand spots an Instagram post from a user praising their sustainable packaging. Seizing the moment, they share this post on their official page, further promoting their commitment to the environment and engaging with satisfied customers.

Social Listening: Beyond the Here and Now

Enter social listening. This practice goes a step further by analyzing broader conversations and sentiments around your brand and industry. Instead of focusing on individual mentions, social listening looks for patterns, trends, and overall sentiments.

Social listening tools are essential for this purpose. They collate vast amounts of data from different platforms to offer insights into how your brand is perceived in the larger context. These tools not only track mentions but also dive deep into the emotions and sentiments behind them.

Take the example of a smartphone brand launching a new model. Social monitoring will inform the brand about individual customer feedback – say, a glitch in the software or a broken screen on delivery. Social listening, on the other hand, will paint a broader picture – is the overall sentiment positive? Are people excited about a specific feature? Are influencers endorsing it? Answering these questions aids in long-term strategy development, market positioning, and even product improvements.

Social Listening Examples in Action

To better understand the concept, let’s look at a few social listening examples:

Product Development: A beverage company notices a recurring sentiment around the need for a sugar-free version. By addressing this through product development, they cater to an unmet demand.

Crisis Management: A fashion brand, through social listening tools, identifies a budding PR crisis due to a controversial product. Before it escalates into a full-blown issue, they address it, either by pulling the product or offering a clarifying statement.

Influencer Collaborations: A skincare company identifies rising organic endorsements from a specific influencer. Recognizing this, they collaborate with the influencer for a campaign, tapping into an already engaged audience.

Why Both Matter

Drawing a line between these practices, it’s clear that while they function on different scales, both are essential for a comprehensive social media strategy. Here's why:

Immediate Action vs. Long-Term Strategy: While social monitoring addresses immediate concerns and enhances customer service, social listening influences product development, branding strategies, and marketing campaigns based on widespread consumer sentiments. Individual Voices vs.

Collective Sentiments: While individual feedback is invaluable, understanding larger patterns helps brands anticipate future market trends and customer demands.

Introducing Brand Intel: Your Comprehensive Social Monitoring and Social Listening Solution

While we live in an era dominated by online conversations, having the right tools to navigate the vast expanse of digital chatter is extremely valuable. Enter Brand Intel, a state-of-the-art social listening and brand intelligence platform that stands out in its offerings. Designed to mine valuable brand insights, it spans across the intricate global web of both social and traditional media channels.

With Brand Intel, companies can do more than just listen; they can understand, engage, and strategize. It's not just about managing brand reputation, but also about truly comprehending the ebb and flow of your dynamic customer base's engagement. This understanding is brought into sharp focus with AI-powered analytics that ensure you're not just in the game, but consistently one step ahead. And with the competitive analysis tools embedded within, you're never caught off-guard.

Let's take a closer look at some of the standout features of Brand Intel:

• Extract insights from a massive global web encompassing over 75,000 sources.
• Monitor topics, products, and campaigns with precision over time.
• Use robust filters like original authors, AI-driven relevancy indicators, and customizable keyword scoring lexicons to pinpoint crucial posts.
• Leverage automated issue tracking and trend recognition for predictive insights.
• Stay updated in near real time, ensuring you're always in the loop with pivotal events and trending discussions. The AI-enhanced classifications act as your smart filter, highlighting key trends amidst the overwhelming digital noise.

Furthermore, Brand Intel isn’t just about capturing mentions; it's about understanding them in context. The insights offered pave the way for optimization across various organizational domains, from marketing and public relations to human resources and legal. The customizable dashboard ensures that companies can swiftly gather, dissect, and act on the data, providing the leverage needed to protect or propel their brand.

Deciphering the Digital Pulse: The Final Takeaway

While the intricacies of social monitoring and social listening may seem nuanced, the distinction between them is crucial for a comprehensive digital strategy. And in an age where online sentiments can make or break a brand, having a reliable platform like Brand Intel by your side ensures you're not just observing but strategically acting on the digital pulse. By integrating real-time insights with deep-diving analytics, Brand Intel equips businesses to both address immediate concerns and forecast larger market trends. In this ever-evolving digital realm, it's tools like these that empower brands to not just survive, but thrive.

The end game of Enterprise Information Management (EIM) is refining raw information into a valuable enterprise asset. What makes information/data valuable is a function of:

• The nature of the information/data in question
• The ways the proprietors of that information/data can envision using it
• The technology available
• The insight, talent, and skill of those charged with executing EIM strategy.

Thus, while it’s common to think of EIM as tech-driven, the most successful EIM strategies are actually far more business-driven than one might expect. Here’s a look at best practices planning and executing an EIM strategy:

Approach it from a pain-point perspective

Perhaps your marketing department is mired in data inconsistencies and duplications, making communications-driven campaigns unwieldy and inefficient. Perhaps the rapidly evolving set of regulations and standards applicable to your business means your compliance program is straining to aim at a moving target. Perhaps you’re a provider, and the six different payers with whom you’re under contract have six different sets of forms and requirements. If you’re thinking about adopting EIM, you probably already have in mind some of the challenges you believe can be addressed through better information management. Such challenges can create concrete business cases you can present to potential executive sponsors and which can form a foundation for assessing the success of your strategy.

Get your stakeholders involved from the get-go

Involving your stakeholders in brainstorming and strategic discussions is, itself, a low-tech form of information management. That’s because EIM is best positioned as a way of supporting critical business activities. Where do your identified pain points interfere with the key business priorities of your stakeholders? How can they be addressed through information management?

Assess your baseline

What’s your baseline level of information management? What are the systems you’re currently using? Who are the vendor(s)? How long are the contractual relationships meant to run? What’s your organization’s approach to information governance?

Secure executive sponsorship

One or more strong executive sponsors can be helpful in securing the necessary funding and support for an EIM initiative. You’ll want to marshal your allies right at the outset, keeping them informed and on-board and available to manage points of friction.

Cultivate enterprise awareness

Congratulations, you understand the need for EIM. But not everyone does. At least not yet. Communicating the need for EIM, the challenges it addresses, unrealized value of information as an asset will go a long way toward readying the people in your organization for the changes envisioned. Overall, your organization needs to be “ready” for EIM, and here are some factors to consider in assessing that readiness.

Adopt a phase-in approach to implementation

You may have a global/big-picture vision of what your organization can achieve as a result of implementing comprehensive EIM, and while EIM is, at its core, an enterprise-wide strategy, it can only be accomplished in manageable bites. But your overall plan should be global and take into account how each phase may affect the next one and the big picture overall. For more specific guidance, each of the factors identified here are equally applicable to EIM as they are to digital transformation in general.

Come up with objective standards for measuring success

The best argument for moving from the first phase to the second and the second to the third, and so on, is results. Ideally, you’ll come up with a way of objectively measuring those results before you begin EIM implementation.

Start with a quick-and-easy win

Starting with a project that’s relatively quick to implement and evaluate, and that’s likely to be a win, will go a long way toward cultivating the continued support and cooperation of your sponsors and stakeholders.

Choose the right partner

EIM implementation requires more than a technology vendor and more than a service provider. EIM implementation requires a strategic partner, one that’s experienced in all aspects of comprehensive EIM planning and implantation. Ideally, your EIM partner will have experience in EIM planning and implementation within your particular industry, as well as in working with customers around the same size as your organization.

As a global leader in business process optimization, Exela works with over 4,000 customers in more than 50 countries and in numerous industries, including banking, finance, healthcare, legal, manufacturing, the public sector. Although we count over 60% of the Fortune® 100 among our customer roster, we work with organizations of all size and on projects of all imaginable scale. We’d welcome the opportunity to talk to you about your organization’s specific challenges and needs.

Data for the Masses

Business intelligence (BI) is no longer confined to bulky centralized data warehouses owned by IT. As the reliance on data and analytics becomes more prevalent across all industries and business types, the need for greater access among different departments and users has grown exponentially. More and more companies are realizing the benefits of decentralizing big data operations to give individuals more power over how and when they access critical business information. This includes the utilization of past, present and predictive analytical data models to address current business challenges and inform decision making in a timely and efficient manner. Facilitating the transition to self-service BI is the proliferation of software elements that support configurable reporting, interactive “slice-and-dice” pivot-table analyses, visualization, and statistical data mining.

While traditional BI models still add value, especially in the case of large enterprises, the need for greater agility is required to keep up with the growing volume of data and sources available. Plus, more access to real-time, data-driven information, has presented businesses with opportunities to pinpoint and address problems across functional areas such as, sales, production, and finance, immediately. Putting the power of data in the hands of the average user can have even greater implications when it comes to future business improvements and competitive advantage.

There is no doubt that businesses depend on data for sound and informed decision-making. To facilitate the proliferation of data among stakeholders and enable on-the-spot business-critical analysis, more companies are investing in BI software and applications. Technologically advanced tools, such as Exela’s web-based, intelligent reporting platform, Athena, provide opportunities for average users, like you and me, to view and manipulate data that, otherwise, might not be readily available. Platforms like this offer analytics and information that is easy to decipher via graphical representations and drill-down features. With the help of self-service BI applications, department heads, or average users can gain valuable insight into all aspects of a business, whether it’s inventory management, production workflow, or SLA tracking. With the right tools, the possibilities are endless.

What Users Get Out of It

Businesses have a lot of options when it comes to the utilization of self-service tools. While some users appreciate the ad hoc reporting features and capabilities, others require more intricate functionality including, the integration of private, local data, and the modification of reports and dashboards. Here is a more in depth look at some of the requirements that businesses have for Self-Service BI.

• Creation of Ad Hoc reports and Dashboards

When it comes to building and accessing data-driven reports, IT has taken a backseat to more intuitive tools, pre-defined report templates, and dashboard objects. With the advancement of technology, what used to be a near impossible task for the average user is now a common reality. Reports can now be easily created and shared among employees (usually within the same department).

• Modification of Reports and Dashboards

Not only can employees create their own reports, but, with self-service BI functionality, they have the ability to change the way information is displayed and reported for the analysis of specific data sets. Users have the power to create specific business criterion and manipulate data in order to create meaningful reports that offer new insight into core business processes.

• Integration of Private, Local Data

Often times, data from external sources, such as excel spreadsheets, or flat files, need to be integrated into existing reports, analyses, or data models. Self-service functions allow for easy integration of local data to expand upon the information delivered by the data warehouse.

• Modification or creation of data models

Some business analysts or advanced users require a self-sufficient environment to produce or modify data models. These users will adapt their semantic model to a business department’s needs without the reliance on IT. This modeling can take place in a metadata layer, database, or a confined environment. The specific approach is dependent on each business’s independent needs.

Conclusion

The concept of self-service BI has revolutionized the way that businesses use data. Without the reliance on IT, critical information is now readily available to heads-of-departments, as well as the average employee for impactful decision making. Powerful intelligence tools and third party resources have facilitated the translation of complex, albeit essential, analytic applications into meaningful and actionable insight. Users are no longer restricted to a one-size-fits all representation of data. Rather, they have the flexibility to manage and manipulate volumes of information in a way that can be easily understood and leveraged. The masses have spoken. Business-critical data is now free from the clutches of an over-burdened IT department, giving stakeholders more power to influence and improve business outcomes.

Businesses, irrespective of their size and domain, require access to information in order to make informed business decisions and develop successful strategies. This information is often derived from data, so we might think that more data leads to more information, so more is better. However, it is possible to have too much of a good thing. Data is only valuable if you can use it, and without proper structuring and management tools such as cognitive search tools, companies can find themselves drowning in data.

At the onset of the “digital age,” enterprises struggled to weed through bottomless pits of data, searching for information in unstructured environments. Employees would spend hours of valuable time that could have been used on more meaningful and productive tasks.

Initially, search results were determined solely by the presence and frequency of specific keywords. Search functions have, of course, improved and changed in many ways since those early days. One of the most important shifts came with the introduction of natural language processing and machine learning capabilities, which today power cognitive search tools.

So What is Cognitive Search?

When it comes to data and information, accuracy and relevance make all the difference. Even with the right keywords and key phrases, you can spend hours looking through and collecting information, and still not find what you’re looking for. With so much data on hand - and more being added by the minute - it isn't easy to extract what’s relevant.

Cognitive search is driven by artificial intelligence (AI) and aims to deliver contextual information that is highly relevant to a user’s search request. Relevancy determinations are achieved by inferring a user's intent and finding patterns and relationships within the data.

How Does Cognitive Search Work?

Natural language processing (NLP) and machine learning are used to mine, extract, and summarize data from different sources, irrespective of the formats.

NLP has some restrictions, as it focuses solely on linguistics, whereas cognitive search follows a language-independent, statistical approach to understanding human information that is fine-tuned by the use of linguistics. Simply put, cognitive search is aligned with users more naturally, providing a 360-degree view of the user journey and their past interactions to personalize the experience.

Here are some benefits of cognitive search and how it can be an asset:

Penetrate Extensive Data Sources

We’ve all heard that data is a valuable commodity in today’s world, but even the best information is no good if you can’t get to it. Cognitive search has enabled businesses to extract information buried within voluminous sources quickly, and more accurately, effectively unlocking the potential value of large, previously daunting datasets.

Improve User Experience and Engagement

Cognitive search doesn’t just make it easier for employees to find valuable information and make smarter choices. A customer-facing cognitive search function can create a more effective, streamlined, and satisfying user experience. One of the biggest turn-offs for potential customers is a website that is confusing or difficult to navigate. Including a search function that accurately directs them to content, based on their intent rather than just the keywords they used, can make a huge difference - especially in jargon-heavy industries.

Access Relevant and Accurate Information

Natural language processing doesn’t just help cognitive search tools better understand the intent of the search query - it also helps the system gauge the relevance of text content like email, blogs, reports, research work, and documents, as well as media content like meeting videos and audio recordings. This helps it do more in-depth research and come up with relevant information.

Enhanced Search Results

Machine learning algorithms help in providing better search results. It touches searches through structured and unstructured data and lends profound, meaningful, insightful search results.

Personalized Recommendations

Users’ previous histories and usage patterns can be factored into each new query, better learning their preferences and interests to recommend content that is more likely to be relevant.

Final Reflections

Using cognitive search tools enhances the user search experience, whether it's for customers or employees. With less time sifting through data, employees can spend more time on their core tasks and customers can feel satisfied that their questions were answered in a quick manner.

Learn more about what cognitive search can do for your business.

If you have any association with the tech industry, then you know that data rules the world. It has become the digital currency and businesses that learn to harness the power of data are the ones who manage to be the leaders. Dig deeper and you’ll find that businesses keen on growth always ensure that enterprise data management is their key strength. Call it information management, database management systems or enterprise information management, data-driven digital strategies have become part of boardroom discussions in enterprise organizations.

What is Enterprise Data Management?

Enterprise Data Management (EDM) is an organization’s capacity to integrate, govern, secure, and distribute data from multiple data streams, online and offline. This includes the ability to accurately and safely transfer data across processes, applications, subsidiaries, and/or partners. Effective information management is no easy feat and can only be accomplished by fully understanding your data and implementing an intelligent EDM strategy.

Why is Data Management Important?

Enterprise Information Management (EIM) is about the overall management of information assets. Data generated by different departments live in siloed systems and can be used to create some of the most innovative solutions for your customers. The trick is to create a data lake and interconnect systems breaking the silo organizational culture. Organizations create their own source of superpower when an additional layer of automation intelligence is added to the data lake creating information flows that can transform business processes.

How Does it Benefit Businesses?

If data drives the world, the ones who can control their data can truly benefit from it. The advantages of having an efficient enterprise data management system are numerous. Some of the important ones are as below.

• - Drive digital transformation: A strong enterprise data management strategy is the first step.
• - Fully leverage data: Control and analyze structured and unstructured data for efficient business processes.
• - Enhance customer experience: Deliver highly targeted and personalized experience to your customers.
• - Improve operational efficiency: Speed up business processes by connecting to the correct data streams.
• - Increase business agility: The right data at your fingertips allows you to respond faster and keep up in the digital age.
• - Improve decision-making: Analysis of the data can potentially turn into the actionable insights needed to improve decision-making.

If data management and information systems interest you, you’d also like our eBook. It’s an insightful report based on interactions with various Fortune 100 companies that happen to be our customers.