Canadian brands like TD Bank, Structube and SickKids Foundation are embracing the computational capabilities of AI and machine learning, and the resulting data is enabling new and accurate consumer insights like never before.
Because AI is so effective in forecasting up-to-the-minute consumer behaviour, brands are rushing to incorporate AI-powered audience solutions, especially in light of the fact that digital ad spending will account for 68.3% of the total ad market in Canada, according to Insider Intelligence.
AI and machine learning allows marketers to gain insights in real time, at scale, empowering them to better understand the needs of their target audiences.
The result: a better online consumer experience that creates brand trust through relevance and, in turn, improves business performance. AI and machine learning are now table stakes in maintaining a competitive edge; global investment in AI for marketing is expected to reach $23.14 billion (US) by 2027, up from its present value of $9.8 billion, according to ResearchAndMarkets.com.
Here’s five ways Quantcast clients are using AI to revolutionize and boost digital marketing impact:
- Real-time predictive modelling and trend prediction
Understanding trends is a huge challenge for most companies. By using AI and machine learning to create real-time models, marketers have a better view of what may happen next. At the very core of the Quantcast Platform is a unique combination of real-time, first-party data, and Ara, a patented AI and machine learning engine. Ara is able to react to the most recent events across the internet and capture ever-changing consumer behaviour, understand consumer interest, and infer consumer intent.
To achieve that kind of intelligence and sophistication, Arauses advanced machine learning algorithms to build custom predictive models for each campaign. In addition to these campaign models, Araalso builds media models for viewability and brand safety as well as general models, such as a TopicMap of the open internet. All this modelling is done using advanced machine learning techniques such as neural networks and, in some cases, deep learning (topic modelling).
- Personalized customer experience
Brands must quickly evolve to capture the emerging digital consumer, moving from a traditional customer model to one focused on the online experience. To reach this next generation of customers with personalized experiences, brands can tap into the power of automation, machine learning and AI, and segmentation to increase brand awareness, change perception, improve web traffic, and grow sales.
For example, BDG (formerly known as Bustle Digital Group), a fast-growing youth-targeted global publishing brand, worked with Quantcast to gain audience insights about how its content is resonating and being engaged with, across all of its sites. Quantcast tools allowed BDG’s editors and writers to think differently about future content based on how audiences respond. When BDG focuses on their audience preferences, the publisher sees rates of engagement up to four times higher than when it does not rely on the data. As a result, Millennial and Gen Z-focused publisher BDG has achieved a larger reach with strong engagement.
- Advanced audience analytics
AI/ML can detect patterns in vast amounts of data, helping marketers make better sense of both the data and their potential customers. The Quantcast Ara TopicMap enables insight into live consumer behaviour, interest, and intent. Ara operates on real-time data, which means it handles massive scale (up to 20-40 petabytes of data processed daily) and can operate at a low latency, or minimal delay.
This is made possible with a data analytics system built from the ground up – one that turns huge amounts of data into an insights playground. It queries a database of over a trillion online signals in under 100 milliseconds to provide an interactive and instantaneous experience. It is this kind of surrounding infrastructure that helps realize the true benefits of AI.
Home furnishings retailer Structube is a beneficiary of advanced audience analytics: when they wanted to increase key Q4 revenue, they developed a full-funnel concept and utilized Quantcast’s performance and brand capabilities to drive customers to conversion. Using promotionally-timed, customized messaging and user segmentation, Structube surpassed a four-time return on their ad spend goal and enjoyed a 65% lift on site visits.
This also extends to non-profit campaigns: SickKids Foundation, in partnership with digital media agency Aber Group, needed to launch and recruit participants for their first annual fundraising “Million Reasons Run” campaign. Calling on Quantcast’s audience and insight expertise, they leveraged the company’s real time view on consumer behaviour to grow their donor pool and drive conversions. It all added up to groundbreaking success: 7,000 home page site visits within the first 14 days; 600 donations, with 8,000 people participating in the challenge and over $2.2 million raised –129% above the original target.
- Greater ability to discern preferences
Large data sets operated on by machine learning not only help isolate patterns but also discern preferences. An important step is to connect marketing to the consumer and individual, and the key is consent. When asked, most consumers actually prefer more personalized experiences. To do this well, consumers need to be part of the conversation, providing consent to use their data for specified purposes so we can deliver more relevant products that align with their preferences.
- Pattern recognition
For effective AI marketing, pattern recognition provides the foundation, allowing marketers to comprehend consumer segments and identify common attributes via demographic-based data analysis, customers’ web-browsing activities and past purchase history. These shared attributes can be amplified by identifying customers that display similar behaviours.
For example, during the early stages of the pandemic, TD Bank needed to understand key changes in consumer behaviour and rapidly anticipate new trends in order to meet their customer’s needs and ensure their mandate of providing “the confidence to thrive in a changing world”. After witnessing a substantial rise in investment products in early 2020, TD Bank relied on the Quantcast Platform to monitor real-time consumer behaviour through Ara, using the results to not only increase the usage and activity on their online trading platform, but also introduce novice investors to TD Bank’s “confidence” messaging – a growth that continues today.
These audience insights from Quantcast proved so valuable that they now provide the foundation for how the brand identifies and targets audiences across other platforms.
As digital marketing heads towards a cookie-less universe, AI and machine learning combined with Quantcast’s insightful consumer expertise is one of the more potent catalysts of Canadian digital advertising’s future.
By Sam Gottfried, Quantcast head of sales, Canada. For info contact sgottfried@quantcast.com
