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How to drive growth with conversational intelligence

How to drive growth with conversational intelligence

We’re stuck in a data overload. Struggling to handle, and benefit from the masses of data that brands and consumers create every day.

To survive, you need to move away from merely crunching data and focus on conversational intelligence. With powerful insights driven by the conversations that matter most to consumers. Here’s how…

Transform your brand with social media intelligence

Definition of conversational intelligence

What is conversational intelligence? To date, a lot of social listening and analytics is about data. Gathering, interpreting, and actioning data from social media, blogs, news sites, etc., on a large scale to create actionable insights.

What we forget when we monitor like this, is the social aspect of social media. People don’t set out to create data. Instead, they:-

  • Build conversations.
  • Share joint experiences.
  • Rave about great services.
  • Rant when things don’t go right.
  • Establish real emotional connections with their family, friends, and followers.

Conversational intelligence goes deeper than social listening. It’s a new methodology, or mindset, that turns daily conversations into actionable intelligence that brands can use to optimize their digital strategy. Not just with social data, but from a wide range of sources from across the company. Creating a single source of truth for the brand.

Before we can appreciate the benefits of conversational intelligence, we need to consider the issues enterprises face when handling consumer data.

Data dystopia - too much data?

It’s expected the world will create about 44 Zettabytes in 2020. A number so big, it’s incomprehensible. That’s 176 flash drives of data (32MB) for every person on the planet.

Conversational intelligence - a day in data

A look at one day in data demonstrates how we create so much data. Infographic by Raconteur. A full-size version is available here.

We’re on the cusp of drowning in data. For enterprise brands, managing all that information about their brand, users, potential market, products, campaigns, competitors, channels, and more, is becoming a significant challenge.

This issue has been at the forefront of business minds for several years, with enterprises focused on digital transformation. Restructuring their technology to handle big data more effectively. With the rise of COVID-19, and the economic aftereffects, this technological transformation is essential for future success. 75% of Fortune 500 CEOs state that the pandemic has accelerated their company’s technological transformation efforts.

The challenges of enterprise data

Big data, and the technology needed to manage it effectively, brings several challenges to enterprise businesses.

Challenge - Unbreakable data silos

Data silos are not new. But they’re still causing significant division across departments, with data either going unused (80% of collected data is untouched) or segmented.

This leads to each department creating profiles and processes based on the data they have. Leading to arguments, inconsistencies, and worst case, wrong decision making at critical points.

Challenge - Lack of data engagement

Data silos lead to gate-kept data. Instead of defusing the data into the hands of users, the people on the frontline, it’s often inaccessible. This could be down to:-

  • Too many data silos (see above).
  • A bottleneck of data being handled by smaller analytic departments.
  • A lack of technical know-how when it comes to understanding big data.

Even if the demand for data is there, an easily accessible, understandable, single source of truth isn’t available to fulfill the need. Over 50% of executives think their business doesn’t treat data as an asset.

Challenge - Inability to enact data-driven decision making

We all know how important data-driven decision making is. Businesses with data-driven strategies drive up to 8 times more ROI than those without. The hard part is getting to those decisions.

The problem here is identifying what should be measured in the business. Many companies still measure just because they can. With 72% of marketers focused primarily on knowledge-gathering, instead of focusing on turning that data into actions.

The fear of missing out leads to irrelevant data monitoring, focused on vanity over business impact metrics. Leading to a lack of comprehension and unscalable systems. This misunderstanding of what has to be gathered and measured, with no clear frameworks for success, keeps brands from reaching their full potential. Inhibiting growth.

Challenge - Ever-evolving digital landscape

Technology is developing exponentially, bringing more opportunities to brands and consumers. In 2020, there are an estimated 3.6 billion social media users across the world. Expected to increase by 22.5% over the next 5 years. Combine this with other technological changes (like 5G, VR, and AR) and we can see how technology will look very different in the next few years.

Staying ahead of the curve comes at a huge cost to productivity and with a significant risk factor attached to it.

Where does conversational intelligence come from?

Conversational intelligence is a development of how brands understand their consumers, but created for the future of digital transformation. A continuation of how brands have traditionally worked, but updated for the 21st century.

  • Traditional market research. Before digital and social media, companies relied on surveys, interviews, and focus groups to gather opinions and perceptions around their brand. They’re still beneficial today, for gathering more niche insights in a personalized way, but is not real-time and oftentimes biased. Which led to…
  • Digital marketing research. With instant, technology-led solutions, brands can now get feedback from clients. Either indirectly from conversations through social listening, or directly through web surveys and online panels.

But this led to the increase of brand data, and the need for numerous platforms to monitor all the data. Until…

  • Conversational intelligence. A single solution is found to manage all that data. Including traditional market research, social listening, and even owned data, from customer service calls and chatbots. Conversational intelligence puts all your data in one place, and enables you to understand it more effectively.

Conversational intelligence - Big data management

Conversational intelligence combines data from across your enterprise, into one, easily accessible, single source of truth.

How conversational intelligence solves the 4 enterprise challenges

Amalgamating all your data is a step towards solving the enterprise challenges. But that’s only the beginning. The way you manage, interrupt and understand data should develop too. Conversational intelligence also helps you translate this newly collated data into a resource usable across your entire brand.

Here’s how it can be used to solve the 4 enterprise problems:-

Solution - Smash data silos

Conversational intelligence can collate cross-departmental data, so you no longer need a solution for each team. This builds a company ‘data lake’ - pulling data from numerous streams to flow across the whole company. This means that your entire business can leverage the same single source of truth, unifying decision making across all departments.

Solution - Create company-wide data engagement

This unified data source means there is no longer any gate-keeping. All team members can access the same data to make their role work harder. Though it doesn’t mean simplifying data.

Instead, data segmentation provides customized dashboards and reports targeted towards the user. Ensuring that each member of staff has the precise insights they need, from groundlevel to C-Suite. Creating a company culture based around data and engagement with it.

Solution - Enable data-driven decisions

Accessible data is one thing. Understandable data is another.

Conversational intelligence is about understanding conversations at scale. Taking the big data and turning it into actionable insights. Making the most of machine learning to automatically categorize information, enabling the sorting of millions of conversations, to highlight those that are most valuable.

Powerful visualizations are also key. Converting that conversation data into visual stories, that can be quickly reviewed and understood, for users to spot correlations, trends, and insights.

Conversational intelligence - Conversation Clusters

Conversation Clusters is a user-friendly data visualization tool that helps you instantly uncover, understand, and visualize the context around any topic at a glance.

Solution - Equip companies for the future of big data

Conversational intelligence is a key part of companies developing digital maturity. This ongoing process helps companies prepare for the evolving technological landscape.

As conversational intelligence is an adaptable mindset, designed to incorporate the growing use of data, it has the flexibility to grow over time. If a new critical data source emerges, it can be quickly incorporated into established processes. Using machine learning at its core, it enables scalability at an enterprise level.

What conversational intelligence will do for your brand

So far, we’ve looked at conversational intelligence in broad strokes. But what impactful changes can it be used for across your brand, right now? Here are 4 major use cases that you can develop through this evolved methodology.

Campaign management

Integrating all your campaign analytics, including owned, earned, and paid data, with other sale-identifying data, helps you monitor your campaign results in real-time. So you can see how campaigns are directly influencing consumer conversations.

Did it create a buzz on social media? Did consumers pick up your key messages? Are you directing buying signals or seeing sales hit your bottom line?

When budgets are tight, this will enable faster campaign optimizations, so you can focus your spend on what’s working and cut what isn’t.

Voice of the customer

Voice of the customer (VoC) is a analytics technique that gives brands a comprehensive understanding of the customer needs and wants by analyzing customer feedback. Helping them bridge the gap between their customers’ expectations and actual experience.

Conversational intelligence encapsulates this, understanding of the human aspect of VoC, by compiling the pieces of customer data from across the enterprise and putting them together as a complete picture.

Conversational intelligence - Voice of the customer

How conversational intelligence can be used to collate data to complete your voice of the customer.

This enables brands to respond, improving their customer experience to meet growing needs. Not only for marketing purposes, but to create more proactive complaint strategies, reducing potential risks, and helping to manage the costs of customer service teams.

Market intelligence

Market intelligence helps decision-making when it comes to developing and growing a business. From seizing opportunities with new products or initiatives, increasing your brand’s share of market, or developing strategies to expand into new market segments. This includes consumer intelligence and category insights.

This often relies on trends and predictions - seeing a gap in the market before your competitors. Conversational intelligence, supported by advanced machine learning, creates a close-to-comprehensive picture. Making it easier and faster for people to spot these trends, and action them first.

Reputation risk

Brand crises can now originate from any direction. Mistimed marketing campaigns, faulty products, customer complaints, fake news, ill-advised influencers, even inappropriate messaging from the C-Suite, can all spin into a disaster.

Conversational intelligence enables you to monitor all aspects of your brand, with the support of machine learning to flag issues before they escalate. Plus, if a crisis does hit, you can have all the information around it to handle the situation immediately, to ensure your response hits the right mark.

Why Talkwalker is investing in conversational intelligence

“The power of understanding what consumers are saying, where they are saying it, and why”

Talkwalker is designed for advanced conversational intelligence, with a powerful platform, supported by continued investment in machine learning. Created from the ground up, to meet the growing needs of enterprise brands across the world, with the highest level of data gathering, and easy to understand visualizations.

Leading to a platform that can:

  • Understand conversations in context by analyzing social, media, customer and consumer data in one place.
  • Translate conversations into actionable insights through AI-driven analytics.
  • Solve enterprise use cases through proven methodologies and flexible frameworks.
  • Develop alongside your brand and its needs, as a strategic partner.

To discover more on how your business can activate conversational intelligence across all aspects of the business, ask for a free demo.

Conversational intelligence - CTA