Conversation Insights illuminate brand blind spots and unlock hidden value in customer data

“Data” may be one of the most-used words in marketing and brand management today, but a recent NewVantage survey shows that only 26% of companies claim to have built data-driven organizations.

Other estimates paint an even grimmer picture. Forrester Research finds that anywhere from 60% to 73% of all enterprise data goes unused for analytics. And it’s not for a lack of effort: 92% of companies are accelerating their investments in Big Data and AI in 2022.

We can draw some important conclusions from these statistics:

1. There is a universe of untapped customer data that could have a huge impact on your brand

2. Organizations understand the value of that insight and are willing to devote resources to it

3. There remains an enormous barrier between the raw data itself, extracting value from it, and taking action

Why do brands struggle to extract value from data?

Every brand is unique, but those that struggle to turn data into actionable insight often face common challenges:

• Poor visibility of key data sources. It’s hard to find value in your data when you don’t know what you have. These blind spots apply to data you collect but don’t leverage, but they also arise in social channels like X, formerly Twitter, where many brands miss out on important themes that emerge from customer conversations simply because they don’t know what to listen for or how to capture it.

• Time-consuming data analysis. For most large organizations, making data ready for action requires layers and layers of manual process. That inefficiency means that by the time your brand teams have the information they need, the situation it describes has changed. Trends have moved on, customer sentiment has changed, and opportunities have been missed.

• Inability to generate granular insight. Most brands can’t drill down into data to better understand what it’s telling them about customer feelings, needs, and preferences. That means marketing teams can’t create targeted campaigns, analysts can’t understand customer nuances, and brand managers can’t anticipate market changes that might create reputational risks.

• Fragmented ecosystems. Most brand teams work in silos and use multiple point solutions. That means they often generate competing interpretations and lack the ability to efficiently coordinate efforts or even know where to turn to get critical questions answered.

Given these barriers, it’s no wonder that so much data goes unused, especially the unstructured social data that informs major consumer trends and behaviors. Let’s focus on that data to better understand how the right tools can help you unveil your brand's blind spots and close the gap between raw social data and relevant action.

What is conversational data?

There’s a subset of social data — conversational data — that is vital to brands because social channels are where your customers are having real conversations about the things that matter most to them. Sometimes, that revolves around a purchase or consumer experience, and it might even include your brand. But far more often, your customers are talking about world events, celebrities, art, movies, and all the other elements that make up a culture.

That culture, the interactive dialogue among communities, and the way those discussions evolve over time have a powerful influence on the decisions customers make. A well-placed, expertly worded advertisement might reach someone at the perfect moment to inspire a purchase, but the overall needs or desires behind that purchase are shaped by interactions that don’t directly involve a brand.

Social listening is an important tool to capture real-time consumer data relating directly to your brand, using keyword-based machine learning to identify in-the-moment insights. Conversational data builds on that foundation, leveraging powerful, unsupervised AI to reach beyond keywords, tap into those culture-level discussions happening across digital channels, and derive a richer understanding of your customers.

What are the deeper customer insights my brand needs?

Intelligence derived from conversational data helps you recognize higher-order interactions among customers so you can understand the macro and micro trends that inform their choices. This kind of information can be utilized at both the strategic and tactical level to engage your customers in more targeted, authentic ways by accessing:

• Unmet needs. Customer conversations across social channels can organically surface preferences and pain points that won’t show up in keyword-only listening. This data can be shared with your marketing team, helping them to craft focused messages that target underserved needs; with your R&D or product teams to incorporate new features to meet those needs; or with your PR and corporate comms teams to alert them to potential reputational risks.

• Trend formation. Conversational data help brands understand how and why trends form because they allow you to drill deeper into data to understand the emotions, moods, activities, or occasions that coalesce around a theme. You can harness these inner workings of a trend to get out ahead of it and take action more quickly.

• Trend relationships and evolution. Multiple trends often create influence over the marketplace in combination. For example, 2020 saw huge spikes in conversations about social justice, mental health, and the future of the workplace. At a surface level, these are three separate conversations, but as we all experienced, they interacted with one another in unexpected ways. With the right insight solution, your brand can visualize these relationships, analyze patterns among them, and see how those relationships change over time in ways that are important to your customers.

• Subtopics around major themes. By tapping into subtopics at the periphery of major trends, you gain finer insight into niche conversations related to that overall theme. With this kind of data, your brand can better understand nuances among demographics, geographies, or sentiment — so you can create more targeted messages, prioritize marketing strategies, or tailor product offerings to specific market segments.

Uncover macro consumer themes you might have missed with Conversation Insights

For years, Sprinklr has worked with major brands to help them tap into real-time insights — while empowering them to act in real time, too. Your brand can now apply that expertise to the most important trend-driving conversations taking place among customers with Conversation Insights.

Part of Sprinklr Insights, Conversation Insights reduces time-to-action for consumer insights, social intelligence, and market research teams with:

• Powerful unsupervised AI that goes beyond keyword-only listening to generate conversation clusters at a macro level, so you can understand how different trends and themes emerged over time, giving you a window into unseen insights and allowing you to take action

• Automatic data analysis that eliminates reliance on slow, wasteful manual process, like sifting through pages and pages of customer verbatims or trying to identify the next big trend across millions of social posts

• Clear, visual-based reporting that allows you to see nuanced relationships among trends and drill down into data for a more granular understanding of your customers’ emotions and needs

• Time-lapse capability so you can visualize the ways different trends have changed over time and anticipate what comes next

• The only unified customer experience management (Unified-CXM) platform that gives every brand team a single source of truth and the power to act in a single solution

No matter what trends impact your customers, the time to act is now. Contact us today for a demo and learn more about how Conversation Insights can help uncover your customer-data blind spots and close the data-to-action gap fast.