In the rapidly evolving business landscape, Artificial Intelligence (AI) has become a game-changer for organizations across various domains, including Consumer Insights (CI) teams. Leveraging AI for consumer insights can unlock valuable data-driven insights that lead to informed decision-making and a competitive edge. However, to effectively navigate the world of AI, CI teams must adopt specific research skills. In this blog post, we will explore five essential AI research skills that Consumer Insights teams can embrace to leverage AI technology effectively.

1. Data Sources: Tapping into External and In-house Data

The foundation of successful AI analysis lies in the quality of the data used. Consumer Insights teams should identify and utilize various data sources to gain comprehensive insights. This includes internal data and authentic external data from third-party providers. For instance, online consumer review data can come from online retailers like Amazon, Walmart, Sephora, and others. This type of data contains essential information that can be fed into AI algorithms for analysis.  At this point, it’s critical to ask whether the data from external sources has been cleansed to ensure accuracy. Erroneous data and duplications can skew results and impact business decisions.

External data provides broader industry insights and benchmarks performance against competitors, while in-house data offers a unique understanding of the organization’s specific customer behavior and preferences. Integrating both data sources enables Consumer Insights teams to obtain a holistic view and make data-driven recommendations that align with business objectives.

2. Customer Success: Partnering with the CS Team

Integrating AI products into Consumer Insights can introduce complexity, making it essential for CI teams to collaborate with their Customer Success (CS) team. The CS team can provide valuable guidance on understanding the AI platform, its features, and best practices to maximize its potential within the Consumer Insights context.

Engaging with the CS team from the outset ensures a smooth onboarding process and minimizes the learning curve for Consumer Insights professionals. This collaboration empowers the CI team to derive optimal value from the AI platform, thereby improving the efficiency and accuracy of their insights.

3. Combining Different AI Products: Amplifying Analytical Power

AI is a diverse field with various applications. Consumer Insights teams can unlock the full potential of AI by combining different AI products to amplify their analytical power.

For instance, utilizing generative AI tools for both pre-purchase and post-purchase insights can provide a comprehensive understanding of consumer behavior throughout the customer journey. By integrating multiple AI solutions, CI teams can uncover deeper insights, discover hidden patterns, and gain a competitive edge in understanding consumer preferences and behaviors.

4. Test and Expand: Embracing New Tools Confidently

Consumer Insights teams should proactively experiment with new AI tools and technologies as the AI landscape evolves. Embracing new tools can provide valuable insights that were previously inaccessible.

To minimize risk, CI teams can start with temporary contracts or subscription-based models, allowing them to measure the impact of the tool on engagement and productivity. By closely monitoring the Return on Investment (ROI), teams can make data-driven decisions on whether to expand their usage or explore alternative options.

5. Self-Confidence and AI Faith: Trusting the Results

For Consumer Insights teams to derive maximum value from AI, they must have confidence in the AI tools they employ. After thoroughly understanding the data, algorithms, and technology, it is crucial to trust the results generated by AI.

Rather than doubting the outcomes, Consumer Insights teams should treat AI as a powerful source of data and insights that can enhance their decision-making process. Embracing AI results as valuable inputs can lead to more accurate consumer understanding and informed business strategies.

Conclusion

AI has become a crucial tool for Consumer Insights teams seeking to stay competitive in a fast-paced market. By mastering the essential AI research skills outlined in this guide – utilizing diverse data sources, collaborating with the CS team, combining AI products, testing and expanding new tools, and having faith in AI outcomes – Consumer Insights teams can harness the true potential of AI technology. Embracing AI with the right approach will empower CI teams to make well-informed decisions, optimize their consumer understanding, and ultimately drive business success in the dynamic consumer landscape. To learn more about how Revuze leverages AI, click here.

Florence Broder