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Companies generally use AI to automate repetitive tasks, generate and personalize content, identify performance and operational patterns, and identify many things.
It is clear that AI is already helping businesses cut costs and save time. But they often apply AI to individual tasks across their business. Only when these isolated efforts are aligned to support a broader strategy that can unleash greater impact.
This shift from AI as a purely tactical tool to strategic partners is where companies have the biggest impact on revenue.
As CEO and Founder of a Global Technology Company, I saw firsthand how AI not only accelerates the market transition, but also changes the way businesses interact with their customers. Infragistics leverages AI to enable other organizations to do the same thing. This identifies ideal customers for new and existing products, crafts and test messaging, particularly those that resonate and measure performance in real time.
However, the AI-powered market strategy is just as powerful as the data behind it. So, why data is at every core we do as a company, and why we built a data-driven work management platform that puts the Slingshot: data-driven work management platform at the heart of our organization. With all your company's data in one place, easy to access and integrated into your team's daily workflow, AI is exponentially powerful and its recommendations are much more practical.
Here are how companies can build powerful AI foundations to effectively target audiences, refine their messages, optimize spending, and increase revenue.
Related: How AI Tools Make My Company Stand out in a Busy Market
1. Set clear AI goals
AI has research, analysing data, making recommendations, and predictive trends. All support market strategies. However, for AI to do this effectively, there needs to be a clear direction. Is your company launching a new product? Are you entering a new market? What will success look like in six months? In a year? And how is progression measured?
If we can make it clearer, it could be a more strategic AI. Teams improve performance when they understand how individual roles within the company contribute to the larger company's goals. AI also needs to agree with that.
We prioritize regularly communicating business and long-term goals between teams, so everyone knows exactly what they are working on. And with Slingshot we took it a step further. We have created purpose-driven templates for key use cases such as channel-specific marketing campaigns, growth hacking, and product launches. This allows teams to stay side by side.
With a clear purpose, AI helps identify customer needs, refine your ideal customer profile (ICP), recommend taker messaging across customer segments, recommend campaign timing and channels, measure performance continuously and optimize accordingly. Without understanding the big picture, both the team and the AI will pass the movement.
As teams rely more on AI to complete these tasks, there are not only practical insights to remove more repetitive research and time-consuming analyses from the plate, but also practical insights to move faster and make more informed decisions.
However, for AI to do this effectively, it requires immediate access to quality data. Everything is in one place.
Related: Why Smart Entrepreneurs Have AI Doed Heavy Business Lifting
2. Disassemble the data silo
AI is nothing without data. Most companies know this, but almost half (45%) of employers say they have not yet implemented AI because their company data is not ready. However, being “AI-Ready” is not just about high-quality data. It's about making that data centralized, connected and accessible across the organization.
Business data often live in silos. This spreads across marketing platforms, CRM, ERP systems, spreadsheets and more. With data scattered across these organizations, AI can't see the big picture. This limits our ability to generate insights, spot patterns and provide meaningful value to the company.
To effectively support AI's strategy on the market, it requires a unified view of the business, from customer and marketing data to sales and operations.
With Slingshot, all of our data (parties, platforms, and channels) is in one place. This allows teams to easily review the data we have, access it accurately when needed, and analyze it in real time.
If it takes an average of 35 minutes to analyze three separate data sources (such as Google Analytics, Google Ads, Salesforce), it takes 10 minutes in Slingshot, including sharing insights with your team and assigning the next step.
This myopia analysis allows AI to start delivering value immediately. Find trends across your customer journey, provide real-time insights, and create smarter and faster recommendations.
The Centralized Data Foundation works with teams that enable AI to inform the best decisions for the business, empower them to act as real collaborators, and turn these insights into action.
Related: These are the 50 best AI tools currently
3. Turn AI into a reliable collaborator for your team
The impact of AI ultimately depends on how well the insights your team generates. Especially when implementing strategies to the market.
In many cases, the AI output remains unused. In fact, only 44% of employees say that AI productivity is increasing dramatically in Slingshot's digital work trends report reveals. This could be due to employees' hesitation to adopt AI and fear it will replace them, or lack of confidence or inadequate training in recommendations for AI to effectively implement technology.
However, AI is not about replacing employees, but rather to amplify the possibilities. It can uncover opportunities, support decision-making, remove management lifts, and allow employees to focus on higher levels of strategic work. This means testing messaging across customer segments and relocating budgets based on real-time feedback.
All AI requires human input to be meaningful. Teams need to understand, interpret and act on the surface of AI. This means that not only should organizations provide the right tools, but they should develop a culture where teams are encouraged to experiment with AI and understand the role of AI as collaborators rather than as alternatives.
Timing, targeting and iteration are key to success by acquiring market strategies. AI has the potential to maximize how a company plans and executes at every step. However, success is not achieved through the use of AI alone. It's about doing the same thing by integrating AI into how you think, work and grow your team. When businesses lead clear goals, centralized data and empowerment teams, they can unlock the full potential of AI and continue to deliver business results.
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