Learn how to use your research into buyer behavior to create a winning marketing strategy.
It’s time for our final series entry, and we’re going to take everything we’ve learned and crank it up by a power of ten.
You understand, now, who your leads are and how they’ve thought and acted thus far. Now, it’s time to figure out how they’re going to think and act in the future. This is where intent-based marketing shows just what it’s capable of and starts saving you time, money, and leads.
An effective intent-based marketing strategy combines prediction algorithms and profile modeling, which can be incorporated with artificial intelligence (AI) for an effective automated marketing strategy.
Building an intent-based marketing strategy that leverages your data with software investments
You’ve got data. You’ve got trends. Now it’s time to put all of this to work.
You know who typically shows interest in your product, what content they crave and when, and their behavior once they’re there.
Here’s three steps to make that knowledge actionable.
1. Factor search intent into your content
To do that, you need a strong understanding of how Google and search engine results page (SERP) rankings work.
There are two types of search queries:
- Informational queries ( e.g., “what is ERP software” ) are best addressed with content focused on awareness.
- Transactional queries ( e.g., “where can I buy ERP software” ) are best addressed with content geared toward consumers further along in the funnel.
Make sure you’re producing different content that hits keywords for both of these types of queries, and the funnel stages they address.
2. Use your understanding of user intent to guide your leads’ search
If I were to drop a link here to art gallery software, I’d technically be building backlinks. Did you click on it, though? Most likely not. This defeats the purpose of backlinking, which is to guide your users and their search.
If I were to drop a link to data management software, you’d be much more likely to click since it’s more relevant to this article, and what you’re looking for.
How can you apply proper backlinking to your own marketing strategy, though?
Let’s say you notice that your users are clicking back and forth between two different types of software, and spending lots of time on each, chances are they’re trying to gain a better understanding of the differences between them.
You can provide content that clarifies which would be better for which use cases and then link to both software types. This is useful for both the reader (as it helps them gain clarity) and you (as it helps move leads closer to conversion).
3. Take it to the next level with personalization
Combining personalization software with AI designed to incorporate your understanding of your leads’ deep behavioral patterns makes the difference between good and exceptional intent-based marketing.
Only 34% of respondents to a 2018 Gartner survey said they were using or piloting AI in their digital commerce.
Because your competitors aren’t adopting this tech yet (though they will), this is your chance to get ahead of the game, not only by curating personalized content but doing so in a way that yields a higher conversion rate, higher ROI, and higher customer satisfaction. In fact, 70% of respondents claimed that AI helped increase customer satisfaction.
Start investing in software
So far in this series, your next steps have been additional reading and reworking your personas and customer journey maps.
Now, it’s time to take big action. It’s time to invest in software that can help you along your predictive path.
But what to invest in? Take a spin through these four software types, figure out your budget, and start marketing with intent:
- Personalization software
- Artificial intelligence software
- Knowledge management software
- Predictive analytics software
Results presented are based on a Gartner study conducted to understand adoption and investment plans of AI in digital commerce. This study also sought to understand the value, success of AI in digital commerce and its challenges.
The primary research was conducted online during June 4 to July 17, 2018, among 307 respondents in North America, Latin America, Western Europe and Asia/Pacific.
Qualifying organizations span various industries excluding Healthcare. Companies were required to have primary technology approach for digital commerce as ‘Custom built commerce platform’ or ‘Packaged commerce software solution’ with some(>$0USD) revenue generated from digital channels in fiscal year 2017. Companies were also required to be currently using or piloting AI in its digital commerce. The sample represents organizations in US/Canada (n=86), Brazil (n=35), France (n=30), Germany (n=31), UK (n=30), Australia/New Zealand (n=30), India (n=33) and China (n=32).
All respondents were screened for involvement in strategic decisions for digital commerce within their organization. Quotas were applied for countries, industries and enterprise-wide revenue from digital channels for fiscal year 2017.
Artificial Intelligence: AI is a combination of advanced technologies that change behaviors without being explicitly programmed, based on data collected, usage analysis and other observations. Machine learning is a key technology category driving AI, and includes techniques such as linear regression, decision tree, Bayesian networks and deep neural networks.
The study was developed collaboratively by Gartner Analysts and the Primary Research Team who follow Commerce Technologies & Experiences.
Disclaimer: “Results do not represent “global” findings or the market as a whole but reflect sentiment of the respondents and companies surveyed.
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