To future-proof your brand, you need to keep pace with consumers that change their minds, preferences, and behaviors daily. It’s why having a proper consumer intelligence strategy is no longer a nice-to-have, but a need-to-have. It’s also why AI-enabled consumer intelligence (AICI) platforms have come on the scene (and caused many brands to move from traditional social listening tools to these more robust platforms). They help insights pros harness data from multiple sources (social, search, survey, and more), and do so more efficiently by applying advanced AI and data-mining algorithms.
AICI has also made social data more important and more valuable to a growing number of users. While social media was once only useful to social marketing teams, AICI platforms now power global social intelligence programs by using AI to detect trend signals, flag potential crises, and spot innovation opportunities. Plus, they create the foundation for businesses to make better, faster decisions with a single insights platform.
But building a successful social intelligence program requires more than a software tool. You’ll need new teams, training, and cultural change. Here are four tips for making the case – and managing expectations – for your initiative:
- Start with near-term benefits and quick wins for teams across your organization. Establishing a central source of consumer insights will immediately help teams whose jobs already require them to understand consumers. For dedicated insights and market research teams, AICI platforms bust through traditional blockers by reducing the time it takes to get insights, improving data quality, and identifying market changes sooner. For brand professionals and creative agencies, AICI provides a finger on the pulse of consumer sentiment and trackable metrics, so they can make quick improvements to brand awareness initiatives, PR efforts, campaigns, partnerships, and more. Meanwhile, product and innovation teams can make smarter decisions about possible expansion opportunities by understanding emerging consumer needs and market share potential.
- Chart your path to long-term benefits and value creation. Reducing subjective decision-making by centering real-time consumer insights in every business decision will yield more profitable results over time. By consolidating disparate insights initiatives into one social intelligence program, you’ll reduce redundancy in tech spending and employee work, and create a technology foundation you can build on over time. While getting insights, brand, and innovation teams on the same page around business questions, consumer needs, and market direction will take time, it will lead to better products and services – and improved speed and agility.
- Factor in the direct costs and indirect costs. The cost of buying a platform is a given, but what about professional services? Do you have the data science resources and expertise in house to extract insights and recommendations from massive datasets? Or do you need outside help from data and analytics experts that can apply the right cultural, regional, or industry-specific context? Some vendors provide self-service solutions while others take a “hybrid” approach by integrating custom models and services to help you get the most out of your data. Use case-specific frameworks empower teams to apply consumer insights to their specific domain (e.g. Brand Intelligence or Crisis Management), but expect to invest in training on new processes and ways of working to make real-time, consumer-generated data a part of their daily work.
- Plan for potential challenges. A cross-enterprise social intelligence program will require integrating currently siloed data sources and processes – and ensuring data-quality is up-to-par to deliver accurate insights. And, if your organization has become accustomed to unreliable insights or doubt the value of social data, you’ll have to build trust in data before leaders start using it to make smarter business decisions. For strategy, brand, and innovation teams that have relied on an inside-out approach to decision making, reorienting to a consumer-centric (and data-driven!) business will require new skills and mindsets.