![](https://www.aitimejournal.com/wp-content/uploads/2024/06/GUEST_NAME_AITimeJournal_Interview_1200x630-2-1-1024x538.jpg)
In the dynamic world of marketing, the integration of artificial intelligence (AI) has become not just a trend but a transformative force. Valeriya Pilkevich, a seasoned marketing analytics expert at Kantar, has witnessed firsthand the seismic impact of AI on marketing strategies. From her experiences with Fortune 500 companies to innovative solutions developed for clients, she shares invaluable insights into the challenges, successes, and future trends shaping the marketing landscape. Join us as Valeriya unveils the untapped potential of AI and its profound implications for the future of marketing.
Valeriya, could you share a pivotal moment in your career when you realized the transformative potential of AI in marketing?
During my Master studies at Goethe University Frankfurt (M.Sc. in Marketing Analytics). There was a professor who also worked in a large German bank and he shared the (anonymized) customer data for us to develop predictive models in R to predict which customers are likely to churn and cross-sell. It was magical seeing how detailed such models could actually be. And after the generative AI came to picture a few years ago, I was certain we are just at the beginning and the potential for marketing is immense.
As someone who has worked extensively with Fortune 500 companies, what are some of the most common challenges these organizations face when integrating AI into their marketing strategies?
- Data Silos: Often, data is scattered across different departments and systems, making it difficult to create a unified view for AI to work with.
- Talent Gap: Often marketing employees lack data literacy. And there are hardly any employees who understand data and are able to evaluate its quality and suitability for large-scale AI projects (like Marketing Mix Modelling for example).
- Change: Overcoming internal resistance to change and fostering a data-driven culture is essential for successful AI adoption.
- Ethical Considerations: Ensuring AI is used ethically and responsibly, especially with quickly changing regulations (like the new AI Act in Europe).
Could you describe a successful AI solution you developed that significantly improved a company’s marketing outcomes? What were the key factors behind its success?
I developed a lead gen chatbot for a marketing agency, which improved their conversions by 20%. The idea behind a chatbot: Incoming to the website customers are suggested to take a quick survey to evaluate the potential gain of corporate storytelling for them and areas they need to work on. At the end of the conversation they are asked to provide their emails and business names which are automatically captured and transported to a CRM system. Potential leads get a customized report and the agency gets pre-qualified and warm leads, ready to take the next action. Key factors behind success were: clear requirements from the client, openness to experiment and digital mindset.
How do you approach designing hands-on training and workshops to ensure that participants not only understand AI concepts but can also apply them effectively in their roles?
Before the beginning of the workshop, I try to understand the target audience: their current level of knowledge, their occupation (business owners, employee) as this determines the tools they are going to use in day-to-day, and the use cases they are most confronted with (like pitch deck creation, writing Linkedin posts, repurposing content, writing emails, etc.). This already provides a great foundation for hands-on training. During the training itself I encourage participants to not just listen and watch, but to actually repeat things after me (like prompting, creating automation workflows, etc.).
In your experience, what are the most impactful AI and automation trends currently shaping the future of marketing?
Agents. They can be programmed to execute specific marketing tasks autonomously, like scheduling social media posts, collecting and analyzing data from various sources, enriching lead lists, launching email campaigns, or even adjusting ad bids in real-time based on performance data. This frees up marketers to focus on higher-level strategy and creative tasks.
Could you elaborate on a particularly innovative use case of AI in marketing that you have worked on? What made it stand out?
I’m currently working on building AI Sales agent for the client. He wants to completely automate his sales process, like finding leads, enriching them, segmenting, sending tailored messages, replying to emails, and booking appointments. This is not a simple project as it requires a lot of testing and reliance on technology, which is quite challenging for now (to rely 100% on technology).
What are some misconceptions businesses often have about implementing AI in their marketing efforts, and how do you address these during your consultations?
AI is too expensive/complex: There are many affordable and user-friendly AI tools available for businesses of all sizes.
AI is a magic bullet: AI is a tool that requires strategic implementation and ongoing optimization to deliver results.
How do you balance the technical and creative aspects of marketing analytics when developing AI solutions for your clients?
I act as a translator between these two worlds. I understand the technical capabilities of AI but also the importance of creativity in marketing. I collaborate closely with clients to ensure AI solutions align with their brand voice and creative vision.
What role do you see AI playing in the personalization of marketing strategies, and how can businesses leverage this to enhance customer engagement?
One of my favorite examples of businesses successfully utilizing AI to provide personalized experiences is Netflix.
Netflix employs powerful recommendation algorithms that analyze user data and preferences to generate personalized content recommendations tailored to each individual user. The company also uses AI to dynamically select the most appealing thumbnail images for each title based on the individual user’s preferences and viewing history.
By analyzing various data sources, including biometric data and contextual cues, AI algorithms can predict what content users are likely to enjoy before they even realize it themselves. That’s super powerful (and even frightening).
Looking ahead, what emerging AI technologies or methodologies are you most excited about, and how do you envision them transforming the marketing landscape?
- Immersive Experiences: AR and VR can create immersive marketing experiences, such as virtual try-ons for fashion and cosmetics, virtual tours for real estate, and interactive product demonstrations.
- 360-Degree Customer View: Integrating data from multiple sources (social media, purchase history, browsing behavior) to create a comprehensive customer profile for more precise targeting.
- Quantum Computing: Combining quantum computing with AI to unlock new levels of insight and innovation in customer behavior analysis and market trends.