Consumers all over the world have been shopping and engaging with brands online more than ever as a result of the pandemic. When your consumers go online, you’re competing for their attention with targeted ads and content that will hopefully edge out the competition.

Your consumers expect more from the internet — they want to see relevant content online from your brand, but they don’t want to feel like they’re being spied on. In order to provide effective, powerful digital experiences, you have to craft them in a sophisticated way without privacy violations.

As a marketer, you can provide these kinds of personalized experiences by understanding context in digital marketing. 

What Is Contextual Marketing? 

So how do we define contextual marketing? 

Contextual marketing is adapting your digital campaigns to your consumers’ changing behaviors and other external factors that could impact their choices. The fundamental, old-school version of contextual marketing is seasonal shopping. For example, every clothing company sells and advertises summer clothing right before the summer season because they know consumers are looking for it at that time. 

A more recent version is targeted ads based on demographics (think consumers’ age or geographical location). Using data science and technology, you can take contextual marketing to a higher, more complex level. Instead of thinking about consumers in broad demographic groups, you can address them personally and directly as individuals. 

Marketers know that all consumers are unique. At any given moment, every person has their own context — the challenge is to understand as much about it as possible to then act on it in a timely manner. 

Finding the Right Tools for Your Contextual Marketing Strategy

Currently, marketers use a number of different tools and methods to understand context and create digital experiences for consumers:

  • Market research tools such as Nielsen that provide data around sales and consumer demographics, which are typically used for segmentation (among other things).
  • Tools to perform A/B testing for content or product recommendations. 
  • Content management systems to create custom content for different consumer segments.

Although these tools are helpful, they do have limitations.

  • Many of these tools have integration/setup processes that take at least six months and require significant engineering resources.
  • Some tools might be easy to implement, but are not scalable beyond a certain number of consumer segments. 
  • Marketing technology is perceived as risky and costly to implement — even as organizations are going through digital transformation.

Effective contextual marketing is definitely challenging. You need the right tools, but the process should be built on a data science foundation. This is why so many consumer goods companies struggle; how many consumer brands have data science teams? Fortunately, there’s a simpler approach to contextual marketing that uses predictive personalization. 

Contextual Marketing With Predictive Personalization

As always, technology can make it easier for you and your team to understand consumer context in order to deliver relevant, personalized experiences for them. At Breinify, we look at it as a process or journey — something we often go through with our partners. The tiers are as follows:

  • Collecting data and identifying insights.
  • Starting simple with dynamic segmentation and testing, as well as customer journey optimization.
  • Leveraging AI in order to scale predictive personalization.

For impactful contextual marketing, you must not only collect data, but also understand what you already have. Every organization is at a different stage of this process. But in general, knowing what data you have available is important for long-term success. For example, some consumer goods brands might focus on collecting and tagging data, but retailers who already have large amounts of data might need to focus on how to use it most effectively. This is usually the expertise of data scientists, but technology can help you do this as well. 

So how does technology use data to create context-based, personalized digital experiences for individual consumers? Predictive personalization technology generally uses AI to identify patterns in large data sets to then predict how consumers are likely to behave in real time. It helps you factor in consumers’ changing interests and external factors such as events or the weather. AI is able to catch patterns that humans wouldn’t be able to –– even a team of data scientists would take a long time to do what AI can do in minutes. 

To make sure your technology is doing the most for your brand, consider looking for a predictive personalization tool that’s powerful, scalable, and lightweight. That way, when you use AI for data-driven, personalized marketing, you can be proactive instead of reactive, capture valuable opportunities that might have been missed otherwise, and see results quickly. 

At Breinify, we do this every day with our partners. BevMo! is one of the largest retailers on the West Coast, and its marketing team is always looking for opportunities to increase sales. It launched a themed “Game of Thrones” wine to line up with the show’s final season premiere, but didn’t have time to build a campaign around the product. Our AI helped BevMo! identify consumers who were “Game of Thrones” fans and showed them targeted product recommendations before the season premiere. It might not have been a good use of resources to design a campaign from scratch, but the consumers who might buy alcohol for watch parties would have been a missed opportunity for more sales. BevMo! was able to delight its consumers and increase sales during that period with very little effort from the marketing team — simply because our AI did most of the work!

The beauty of AI is that once you start using it for predictive personalization, it only helps you get better and better with contextual marketing. Like BevMo!, you’ll be able to build stronger connections with consumers in an effortless way. 

Key Takeaway

As people spend more and more time online and are constantly flooded with marketing messages, they want to be understood personally by your company without feeling like they’re being spied on. To achieve this balance, use AI-driven predictive personalization to implement an effective and impactful contextual marketing strategy. It allows you to see results quickly and build strong connections with your consumers in a sophisticated and nonintrusive way.

To learn more about how Breinify can help you create context-based, personalized digital experiences for your consumers, get in touch today.