Beyond just content generation lies a host of possibilities for Gen AI in addressing marketing challenges. As businesses increasingly leverage generative AI, its potential to support marketers with data discovery, curation, and quality has started to become more apparent.
Gen AI holds promise across crucial marketing domains outside of content generation, including buyer engagement, employee productivity, and data analysis. From enhancing customer experiences with personalized chatbots to streamlining email campaigns, its applications are diverse.
In this blog, we’ll take a look at some of these applications for Gen AI, and the first steps that marketers can take to implement an effective Gen AI strategy.
To hear more about the potential impact of Gen AI on marketing, you can check out the webinar we did with Forester on the topic here!
Where does Gen AI fit into the puzzle?
Businesses are turning to generative AI to help them solve data challenges — in fact, it’s one of the top use cases for Gen AI.
When asked what their most important use cases for generative AI in would be in the next 12 months, 40% of respondents said improving data discovery, curation processing, and data quality. This was just barely knocked out of the top two spots by personalization and employee productivity, both of which came in at 42% according to one study.
4 key areas where Gen AI can support marketers
Delving deeper into Gen AI's capabilities, let's unravel its impact on marketers across four crucial domains where marketing organizations are rapidly adopting Gen AI. Generative AI can significantly enhance marketing performance across the following key areas.
1. Buyer engagement
Audiences are no longer satisfied with the disjointed one-size-fits-all engagements that we've been serving them. They're looking for better customer experiences that are cohesive consistent and tailored to fit their needs and preferences.
Let’s take a look are chatbots as an example. They’re one of many touchpoints that audiences are choosing to engage with brands. Customers are reaching out to get support or find answers to questions, but more often than not they leave with nothing more than a higher level of frustration than when they started. Marketers can use Gen AI-powered chatbots and virtual assistance to guide better conversations, supply content recommendations, and provide learnings from those interactions.
2. Employee productivity
One of the biggest benefits of AI is speed. Most marketers are familiar with the necessary busy work that drains all the time out of our day and takes us away from the more strategic, high-value work we should be focusing on.
By using generative AI to automate and expedite these tasks, teams can save time and improve productivity. Let’s take email sequences for marketing campaigns as an example. Generative AI email assistance allows marketers to create and publish multi-touch sequences with sufficient and appropriate personalization — and it lets them do it quickly.
3. Content generation
Generating content is one of the core capabilities of generative AI. It can help with things like ideation, metadata, and basic authoring – and it can do it in a way that's tailored and data-driven.
Many of us have experienced this marketing struggle to support, personalize, repurpose, repackage, and refresh all the content we have. With such broad demands, it can be difficult for content owners to identify how to prioritize these.
Poor prioritization can mean that highly skilled, expensive content creation efforts sadly result in content waste. However, generative AI can help marketers move faster to create variations of content and leverage real-time AI-powered search to define assets or content components. It can extract massive amounts of digital interaction data to understand people's content preferences, ensuring that marketers are focused on those priority content needs.
4. Analysis and interpretation
One thing we are not short on these days is data. But if you don’t have the right data and it’s not in good condition, it can be really difficult to get the insights you need. Gen AI can help give marketers better access to the data they have.
It can be a struggle to find the answers you’re looking for if you’re not on top of your data. Often, reports and dashboards aren’t updated regularly enough simply because the data and ops teams are dealing with a backlog of ad hoc requests.
Generative AI allows marketing and data ops teams to access data, and create dashboards and reports more easily, so they can spend more time focusing on user interpretation and guidance.
Once users get access to the data they need, the next challenge is interpreting what it means and how to use it. Gen AI can help users become more self-sufficient, and better engage with their reports and dashboards by aiding with summarization and interpreting what the data is telling them, even providing some initial guidance on the root cause, and flagging anomalies and trends to guide marketers toward deeper analysis that might be needed.
How do you get started with Gen AI?
So, there’s plenty of opportunity for Gen AI to support marketers — but before diving headfirst into implementation, there are a few key considerations you need to agree on to build out an effective strategy. Here are a few steps to get businesses started.
1. Align to goals and strategies
The first and most important step is to make sure you're starting with defined goals and strategies that clearly outline what success means. After all, you can't measure success if you don't have it defined, and implementing a new tool without a clear sense of direction can make it difficult to focus your time and resources on the things that are going to provide value for your customers.
2. Prepare your data
The next is making sure that the data that you're leveraging is high quality, secure, and compliant. With Gen AI, the quality of your outcomes is completely dependent on the quality of your data. It goes back to the old ‘garbage in, garbage out’ saying.
Getting to a place of data confidence is no small feat for a lot of organizations but evolving your data maturity and strategy is an essential step to get value out of your generative AI investments.
3. Educate leadership and teams
Training your leadership and teams is an essential part of implementation. If you want successful and happy marketing teams, you need to ensure they have the right knowledge to leverage these powerful tools.
4. Experiment, measure, and optimize
We've all experienced those technology rollouts where the tool doesn't quite behave the way we thought it would. So, it's best practice with any new solution to start small and experiment with pilots. Learn what works and what doesn't, and optimize the tool and processes before leveraging it more broadly.
5. Set clear governance and guidelines
Finally, and critically, you need to ensure that your governance policies are being updated for these new scenarios and that the guidance is being clearly communicated to your teams.
Conclusion
In conclusion, Gen AI stands as a transformative force in marketing, addressing challenges with data quality, buyer engagement, productivity, content generation, and analysis. As businesses embark on this journey, aligning goals, ensuring data readiness, and fostering a culture of learning are paramount. With a strategic approach and continuous optimization, Gen AI becomes a powerful tool to enhance efficiency and innovation. Embrace the possibilities, experiment wisely, and let Gen AI guide your marketing success.
