Leaders in Customer Loyalty, Powered by Loyalty360
Leaders in Customer Loyalty, Powered by Loyalty360
#403: Loyalty360 Loyalty Live | Monique De La Rosa, Ansira
Artificial intelligence (AI) and Machine Learning (ML) continue to be top of mind as marketers are leveraging AI and ML in a variety of ways to improve their customer loyalty programs and strategies. Integration of these technologies into day-to-day workflows is a challenge for many brands, especially when considering potential roadblocks from limited budgets, internal resources, and the ability for these innovative technologies to complement brands’ existing marketing technology stacks.
Loyalty360 CEO Mark Johnson recently spoke with Monique De La Rosa. VP, Data Science and Analytics at Ansira, about the opportunities AI and ML present to elevate customer loyalty programs with more seamless and personalized experiences.
Good afternoon, good morning. It's Mark Johnson from Loyalty360. Hope everyone's happy, safe and well. Want to welcome you back to another edition of Loyalty Live. In this series we speak to leading agencies, technology partners and consultants, and customer channel and brand loyalty about the technology trends and best practices that impact a brand's ability to drive unique experiences, enhance engagement but, most importantly, impact customer loyalty. Today we have the pleasure of speaking with Monique De La Rosa. She's the Vice President of Data Science and Analytics at Insira. How are you today, Monique?
Speaker 2:Thank you so much. It's a pleasure to be here. I'm looking forward to it.
Speaker 1:Well, thank you very much for taking the time to join us. First off, can you give us a little overview about yourself and your current role?
Speaker 2:within CIRA and maybe a little bit about your background as well. Great to know, sure. So I've been in the industry now for a little bit over 20 years. I have worked both agency and client side and my career I started as a analyst supporting direct and database marketing campaigns and then moved over to the digital world where I was able to incorporate digital and then move into data science and advanced analytics. So within CIRA, I manage a group or lead a group called Connected Intelligence.
Speaker 2:We are a shared service organization. We support both the internal organization as well as clients and their organizations, and under my span of responsibility is knowledge management, which is an extension of data governance, which is more of the stewardship. We understand all the data in the environment. We are the go-to people for that type of knowledge Reporting and insights, which is our reporting team, client-facing customization, also consulting on our embedded analytics within our tools, data science and analytics, which is more on what we talked about just a second ago, the advanced analytics and data science, machine learning and then, lastly, an enablement team, which helps us to bring all of those things full circle for our clients and internally.
Speaker 1:Brands are seeking to leverage artificial intelligence and machine learning to elevate their customer loyalty programs and customer experience strategies by creating a more seamless and personalized customer experience. How does Insira define AI and its use in customer loyalty in CIRA, define AI and its use in customer loyalty.
Speaker 2:Sure. So I think our perspective is it may not be entirely unique, but we look at AI as more of assistant intelligence, and it's an extension of our collective intellect, and we leverage it to look across not only our internal data and operations from people, processes and platforms but for our clients as well, and so, from a loyalty perspective, it is some of the things that we've been doing for years, but done in a bit of a different way, a more real-time way, and it's kind of helping to understand the collective nature of the data. What are the, what are the signals the data is sharing with us? And that and an example of that can be how we leverage it to identify what's the best offer, how much people are leveraging, you know, the rewards and the programs that they have access to, and how do we optimize how we communicate to them with those different programs, whether it be through direct mail channels, email channels or even more digital channels like social media, things like that.
Speaker 1:Are the brands that you work alongside with that are leveraging AI and ML successfully to elevate the customer experience.
Speaker 2:I think, looking at the signals in a way that is a lot quicker than we've done ever before in our past, being able to immediately, even in real time, be able to look at a customer that may be standing point of sale and be able to identify from an ML perspective or from an algorithm, identify what their rewards are or kind of where they stand in terms of what they're buying, and even make immediate recommendations right there as they're making a purchase standing online, you know, in one of our retail locations.
Speaker 1:At the 2024 Loyalty Expo, Insira led a workshop on leveraging the power of empathy and customer loyalty. How are your clients exploring and using empathy when leveraging AI into and with their customer loyalty programs?
Speaker 2:Oh, this is a fun one and I love this. So one of the things we know about AI is that it kind of reminds me of that, that very smart and precocious preteen that you have to help to not only understand their intellect but how to navigate that as they communicate with others, with their peer play groups and with you know, as they communicate with adults and you know. So. It's one of those things where being able to leverage AI is the ability to have human intervention, still to rely on it to be an extension of the intellect, but still have safeguards in place which allow human intervention, human touch, to really go in and QA and make sure that how we're communicating, what we're trying to do from a brand perspective, is in alignment with what our goals and objectives are.
Speaker 1:Generative AI. Gen AI tools can be a good fit for enhancing customer loyalty and marketing efforts, which includes enhancing marketing messages that resonate with specific audiences through a targeted personalization approach. Now, how can brands better leverage the opportunity that Gen AI offers them when crafting these messages, but also ensure that the quality control and the ethical considerations are being met as well?
Speaker 2:This is a big one, so I think there are several things that can be done. One we spoke about a little bit earlier having human intervention, always making sure that we have effective guidance and guardrails or governance around how we leverage it from an employee perspective, but also how we train our models to be able to identify biases. Today, at Insira, we have a compliance engine which we run our AI through, so it's being able, again, to have human intervention, making sure that we always keep our eyes attuned, but having a pre-game for understanding what AI means to us, what we're trying to achieve, what are the guardrails that we need to contend for? How do we help to minimize any biases and ensure inclusion, things like that.
Speaker 1:The complexity of integrating AI and ML technologies into day-to-day workflows can be a challenge for many brands. What are some pitfalls that brands can consider, and therefore potentially avoid, when they're looking to incorporate AI and ML tools into their existing MarTech stack?
Speaker 2:Yeah, that's an interesting one too. I think I'm not overestimating the capacity of what they're trying to do. I think planning I think this is where I'm really having sound planning is there when employing strategies that will allow us to understand, you know how to create alerts that will alert us to when processes break down. It's looking at how people work processes today and seeing how to emulate that or improve that with the algorithms that we use. So it can be quite complex. I think it's slowing down. It's really being attuned to what it is that we're trying to achieve. And then looking at the systems that we're employing and their efficacy around, how do we make sure that we are moving forward in a way that supports the you know our objective with that tool and technology, and I think that an example of that could be how we leverage embedded AI in things like Salesforce, making sure that we're not asking it to do things that are outside of its capacity or will yield results that are misaligned with what our objectives are things like that.
Speaker 1:As brands are leveraging AI and ML and data analysis and modeling to gain insights for improving their customer loyalty programs. When you work with brands on AI and ML processes, what have you observed? What is working?
Speaker 2:Oh.
Speaker 2:So hyper-personalization has increased a great deal being able to get a more real-time feel on insights that are happening that we may not have looked at in previous years prior to.
Speaker 2:You know, I come from an advanced analytics background, so being able to leverage AI to look across you know the vast amount of data we have to be able to draw conclusions that we couldn't get at before. So I think that's one of the ways that we've been able to do it. I've also seen data. I think that's a really important piece that doesn't often get as as lifted up to kind of share, which is, you know, I often see us having to explore and understand our own data as we start applying some of these technologies. So we've been in engagements where you know we're supposed to be building something like a next best offer, leveraging clients' data, and we're having to go back and dissect that data. Look at, you know, some of the missing data, kind of figuring out the state of the data in order to even drive some of the efficiency that ML will bring us, defining the data, things like that.
Speaker 1:Brands that are committed to employee engagement and leveraging internal teams in support of customer loyalty must communicate how generative AI can enhance productivity and spark innovation, but also have that employee consideration as well. How do you see Gen-AI adoption perceived among brands that your team is working with today? How do you perceive perceptions potentially evolving as well?
Speaker 2:I think, for the most part, there is a great deal of excitement in the industry whether it's internally or with clients, around the capabilities, across all of the ways that we can use AI today. I do think that there's still some trepidation, especially as it relates to data and data privacy and how we are able to engage data so fully and holistically today, which is what we couldn't do before. So I think it's really around making sure that our excitement is measured and that we're able to make sure that we have the right protocols and guardrails in place as we move forward with leveraging it.
Speaker 1:Looking towards the future, how do you see brands leveraging AI and ML in support of customer loyalty programs and customer experience efforts?
Speaker 2:Oh, I think the sky's the limit. I think as we continue to evolve programs and the way we interact with clients. You know we spoke about earlier empathy and AI, which is really about really making sure that we understand kind of the feature signals and how those things overlay with some of our psychographic knowledge of our customers and how those psychographics sometimes interact with the behavioral presentation of what clients or customers may do. So I think the sky's the limit. I think as we continue again to evolve our programming and understand more about our customers, not only from a behavioral perspective but from a psychographic perspective, I think we'll do immeasurable things with AI and I'm looking forward to us continuing to train that precocious child into an advanced adult.
Speaker 1:What do you feel the biggest opportunity or potentially one thing that brands could do to leverage artificial intelligence or machine learning to the benefit of that brand and their customers?
Speaker 2:I think looking at some of the traditional advanced analytics that they've done in their organizations and seeing how that can translate into a more of a real-time you know algorithmic perspective, right? So it's taking those models that we once used to build, like most likely to open our direct mail, and transforming that into an algorithm that can do that work in seconds. You know, when I started my career, it would take us weeks in order to build a model and test the model. Now we, you know, we have that capability at our fingertips and can do it pretty much immediately. So it's kind of looking at translating, kind of how we used to do advanced analytics, and kind of moving it into the present and the future.
Speaker 1:Do you have any closing thoughts or pieces of advice, anything that we can consider, anything that Ancir may be moving forward with this fall? Well, I think there are a lot of advice, anything that we can consider, anything that Ansira may be moving forward with this fall.
Speaker 2:Well, I think there are a lot of things. I think Ansira right now. We recently acquired both Brand Muscle and Sprout Loud. So I think what's going to be wonderful about the future is bringing together the power of all of that technology into one place and being able to leverage those tools, especially from an AI perspective. I mean, the advanced tools that we have today are just amazing, and we do a lot of beta. You know. We do a lot of beta from a machine learning and AI perspective internally, from chatbots to all types of things that we do to test out ourselves and with our business initially. And, you know, I think rolling out some of those things in the future as we continue to bring together this best-in-class technology is going to be really exciting, not only for the fall, but, I just think, in the next couple of years to come.
Speaker 1:And now it's time for our quickfire questions. We like to keep it to one word or short phrase answers. The first question we have is what word or short phrase do you use to inspire others?
Speaker 2:We can do anything we put our minds to.
Speaker 1:What is your least favorite word that others use?
Speaker 2:I don't know.
Speaker 1:What excites you at work?
Speaker 2:I think solving.
Speaker 1:What do you find tiresome at home or at work?
Speaker 2:Never seems to be enough time. That would be it.
Speaker 1:Is there a book that you've read that you'd like to recommend to colleagues?
Speaker 2:Ego is the Enemy.
Speaker 1:What profession, other than the one you currently are in, would you maybe like to attempt? I would be a chef. Is there something that you enjoy doing that you often don't get the time to do? Travel more. Who inspired you to become the person that you enjoy?
Speaker 2:doing that. You often don't get the time to do Travel more.
Speaker 1:Who inspired you to become the person that you are today?
Speaker 2:I think my parents, and what do?
Speaker 1:you typically think about at the end of the day.
Speaker 2:I think about what I'm going to feed my children.
Speaker 1:And last question how would you like to be remembered by your friends and family?
Speaker 2:As someone who was radically objective, someone who was fair, someone who if I didn't know, you know made a point to learn someone who was kind and led with kindness.
Speaker 1:Well, Monique, thank you very much for taking the time to speak with us today. It was great getting to know you a little bit better and also getting caught up with some of the things that Anseara is working on. It was great to hear perspective on customer loyalty and looking forward to learning more from your team throughout the remainder of the year. So thank you very much.
Speaker 2:Thank you so much, I appreciate you.
Speaker 1:I also want to thank everyone else for taking the time to listen today. We look forward to having you back on additional loyalty live soon. Until then, have a wonderful day.