CEO and co-founder Breinify
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Contextual data delivers personalised experiences

29th Nov 2021
CEO and co-founder Breinify
Blogger
Share this content

You hear it all the time in the world of e-commerce: The most effective marketing targets the right customers with the correct messages at the perfect time.

The reason this cliché is so pervasive is that more relevant messaging is linked to more conversions, sales, and customer engagement. That is the North Star for marketing to consumers and the secret behind the most effective campaigns.

Delivering timely, well-crafted, and well-informed messages that get the attention of consumers is easier said than done. But it’s possible, and especially when you use your data the right way.

Breaking down barriers

A multitude of obstacles makes true customer personalisation hard to achieve. For starters, this type of marketing can’t be done manually. Although smaller businesses with fewer consumers might be able to successfully personalise messaging for multiple audience segments, to go beyond marketing automation and enable dynamic personalisation at scale, marketers have to invest in the right technology.

Marketers need solutions powered by artificial intelligence that can analyse huge amounts of data, thus freeing them up to focus on the bigger picture. With solutions that learn from each new piece of data and automatically shift content and product recommendations to best fit customers’ needs, marketers can spend more time on strategy and actionable insights rather than poring over the data and messaging themselves.

Of course, personalisation has to be tied to specific business goals. For example, are you looking to increase sales? Drive CRM registrations? Boost cart value? With a definite goal in mind, marketers can drive results by tailoring AI rules and algorithms to serve specific purposes.

A matter of scale

Marketers who rely on manual curation of messaging development and distribution simply can’t scale their personalisation efforts effectively. It’s too time-consuming to manage messaging for more than about 10 to 15 audience segments, let alone curate product recommendations and dynamic content for thousands.

Moreover, many marketers don’t fully understand their consumers’ needs because they don’t have access to the right data. As a result, they’re unsure of how to best reach their target audiences and how to personalise content to make the biggest impact.

A lack of real-time dynamic content capabilities makes personalisation even more difficult. When marketers are spending their time creating messaging variations for each audience segment, they severely limit the number of segments they can effectively target.

Despite these obstacles, it’s critical that marketers align their messaging with consumer needs and desires at each stage of the buyer journey. This not only improves conversion rates, but it’s also one of the best ways to improve the e-commerce customer experience at large, which ultimately produces greater customer loyalty.

Data drives everything

Data informs all decisions marketers make today. After all, marketers can’t make decisions based on gut feelings anymore: Instead, data holds the key to knowing your customers better than they know themselves.

After all, customer preferences change rapidly (based on their own attitudes, the weather, location, time, and more), so it’s important to tailor product and content recommendations with this in mind and help them find exactly what they’re looking for at that specific moment.

By using their data to personalise recommendations and messaging, marketers can deliver more relevant experiences that provide more value to customers. With that in mind, here are a few best practices for incorporating data into your marketing strategy:

1. Create a digital transformation plan.

Not every firm has started leveraging AI-powered technologies that turn data into actionable insights. As with any fledgling technology, there are early adopters of AI and firms that continue to rely on analog systems while AI-based tools evolve.

That said, companies across regions and sectors have begun aggressively pursuing digital transformation as a means for delivering better customer experiences, largely in response to the COVID-19 pandemic. This is forcing brands to focus on digital channels to effectively reach their target audiences.

However, if your organisation is still waiting to digitise core functions, you should at least be putting together a plan to guide your transformation. What problems are you facing? What tools do you have at your disposal already? What gaps still exist, and how can you bridge those? What longer-term objectives do you hope to achieve?

The answers to these and similar questions should inform your plan. Once that’s developed, it’s time to take action.

2. Invest in data collection and analysis capabilities.

It takes a lot of heavy lifting to gather data from customers, and you’ll have to invest in the right tools and processes to execute your plan effectively. Right now, you might not have the data you need, or high-quality data, or enough data. Or maybe you have tons of data that’s siloed within your organisation or otherwise fragmented and disorganised.

Don’t worry — you’re not alone. Figure out what data you want to collect and how you want to collect it. Then, look for a solution or partner that can help you collect and tag your data so it’s most useful to you.

There are two types of effective data to focus on: historical and contextual data. Historical data helps identify patterns and behaviours over time, and contextual data accounts for the constantly changing variables that influence real-time customer preferences.

Contextual data is valuable because it’s generated in real time (when the weather changes, a customer’s location changes, or a prospect visits your website, for example). Historical data can teach AI about past customer preferences and help identify patterns on a large scale. For e-commerce and retail brands, historical data is especially useful because it helps marketers understand the cycles in which people buy products. For consumer packaged goods brands, however, historical data is less useful because companies are often missing the transactional data that makes this information valuable.

Collecting this information means you’ll need to invest in the right tools and processes to execute your plan effectively. If you automate the process, you can collect and tag data faster. Having a partner can also help you apply sound data management processes so you have a foundation for continual transformation.

As you think about where to devote your investments, remember that you should use both types of data to power an effective contextual digital marketing campaign.

3. Enable dynamic content and audience segmentation at scale.

Brands that are still relying on manual or analog systems typically can’t curate messaging for more than 10 to 15 audience segments at once. Enabling dynamic content makes the number of audiences you can target virtually limitless while also saving you time.

Essentially, this approach permits you to create templates that AI can fill with the right messaging based not only on consumer segments, but also on individual consumer data.

It can identify relevant products, copy, promotions, and other messaging elements, and insert those elements into a digital layout that is consistent with your brand’s aesthetic and tone. This allows for true personalisation at scale.

Remember that automation and personalisation are not the same. Automation simplifies your processes, and AI learns how to better personalise content every time it receives new consumer data. As it does, you can begin creating tens of thousands of customer segments and gradually get closer to delivering a true one-to-one customer experience.

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