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How to Select and Deploy GenAI Tools to Reach Your Next Customer

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Modern marketers are under constant pressure to deliver results with limited resources. Often, lean teams find themselves following a peanut butter approach to marketing strategy—spread thin and suffering from mediocre results. On top of that, pinning down accurate definitions of target personas is increasingly difficult as consumer behaviors change. Time and creativity, the two active ingredients which make up compelling content, are at a premium amid the current burnout epidemic.

How GenAI Enhances Marketing Effectiveness

GenAI offers to alleviate these pains, if marketing leaders are willing to buy in. Large language models (LLMs) represent the forefront of marketing innovation and stand to improve several ways marketers reach their customers.

Content creation. With the right prompting, GenAI models can create high-quality content for blogs, social media, email campaigns, and ads. By automating the heavy lift of content creation, teams are freed up to spend more time on strategy and injecting creativity into their campaigns. Goodbye, burnout.

Personalization at scale. The average marketer has to context switch all the time. One moment, they are writing a buyer’s guide targeted at chief marketing officers, and the next, they are writing a low-level use case for an end user. Keeping straight what each persona cares about and accurately delivering copy that resonates uniquely with them is labor-intensive. Why not use a data-driven approach to analyze vast amounts of information and serve up personalized talking points for each ideal customer profile (ICP)?

Data analysis and insights generation. AI can process and analyze data much faster than we are able to as humans. Pulling in data from past campaigns, AI can be used to predict the future performance of newly written content so that marketers can iterate toward consistent, highly optimized campaigns.

Effective persona targeting. Referencing large pools of data, AI can form a well-rounded model of each target audience a marketer may want to reach. Then, it can analyze copy to ensure the message and language resonates with that specific persona.

The Case for Using Multiple AI Tools

Diversification is the name of the game. Not just in investing or hiring, but also in choosing the right AI. There is no reason to limit yourself to just one, and here’s why:

Maximizing efficiency. Different AI tools excel in different areas. By using a combination of tools, marketers can leverage each model’s strengths to maximize overall efficiency.

Avoiding dependency on a single platform. Relying on one tool can be risky. Unforeseen product pivots, pricing hikes, or technological limitations can disrupt your marketing strategy. Diversifying your AI tools mitigates these risks and ensures continuity.

Verticalized approach. Different tasks require different tools. For example, broad research can be conducted with one tool, while another may be better suited for outlining and writing. This approach ensures that each phase of the task is handled by the most capable tool.

Adapting to rapid evolution. The AI landscape is evolving rapidly. Sticking to one tool risks being outpaced by newer, more advanced solutions. Using multiple tools allows marketers to stay current and adopt the best available technologies.

Practical Steps for Marketing Teams Adopting AI

To successfully integrate multiple AI tools, marketing teams should follow these steps:

  1. Evaluate and select the right AI tools. Assess AI solutions based on criteria such as ease of use, integration capabilities, and the specific needs of your marketing strategy. Be clear about your reasons for adopting AI tools; “everyone else is doing it” is not a valid reason.
  2. Train and upskill team members. Ensure your team is equipped to use new AI tools effectively. Invest in training and development to keep skills current.
  3. Hire new talent. Look for new hires who are open to using and learning new AI tools. Flexibility and a willingness to adapt are critical traits in today’s rapidly changing tech landscape.
  4. Keep your AI toolset current. Regularly review and update your AI tools to ensure they remain effective. Stay informed about new developments in AI technology and be prepared to adopt better tools as they become available.

Consider the case of Search Influence, an SEO and digital advertising agency, which integrated multiple AI tools into their marketing strategy. By using genAI for content creation, personalization, and data analysis, they saw a 24 percent speedup in Facebook ad creation, while maintaining their high standard for copy. Another example is Blazeo, which leveraged a combination of AI tools to provide actionable insights for their website relaunch.

Conclusion

Generative AI has the potential to revolutionize marketing, offering tools that enhance content creation, personalization, data analysis, and persona targeting. By adopting a multi-tool approach, marketers can maximize efficiency, avoid dependency on a single platform, and stay ahead of the rapidly evolving AI landscape. It’s time for marketers to embrace genAI and use it to reach new customers and nurture existing relationships, making marketing teams more agile and transforming their marketing strategies for the future.

Yaniv Makover is the CEO and cofounder of Anyword, an AI writing platform for enterprise marketing teams. Before Anyword, Makover led technical teams at companies like Siklu Communications and Nokia. Makover has a master’s in computer science and information systems engineering from Ben-Gurion University in Israel.

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