As the amount of data available online continues to grow, so do advanced marketing strategies that businesses can adopt to harness and use all that valuable information. You may be wondering where to start or how to enhance your data-driven marketing efforts.
Here are five trends and how to take advantage of them to move to the front of the pack:
1. Personalized User Experiences
Have you ever logged into your Amazon account and found customized product recommendations based on your shopping and browsing activity? Or found your homepage experience personalized in real time to reflect your online behavior? These are examples of how marketers are using data to understand their customers better and create individualized user experiences.
To adopt this strategy:
2. Predictive Analytics
“Predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data,” according to SAS’ definition. “The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.”
You can apply this approach to advance account-based marketing (ABM), which promotes sales-and-marketing alignment by focusing only on key target accounts that match your company’s ideal customer profile. The goal: better understand which companies are most likely to do business with you. In the B2C world, predictive analytics can help you focus your ad spend on the right people, helping you achieve a higher ROI.
Predictive analytics can strengthen your marketing results by helping you identify:
3. Data Onboarding for Targeted 1:1 Ad Campaigns
Data onboarding is a strategy that’s catching on rapidly. A report by the Winterberry Group, cited in Ad Age, predicts the data onboarding market will reach $1 billion in 2020.
Lotame, a data management platform, defines data onboarding as “the process of transferring offline data to an online environment for marketing needs.” Lotame adds, “Data onboarding is mainly used to connect offline customer records with online users by matching Personally Identifiable Information (PII) gathered from offline datasets to find the same customers online.”
You can use such a platform, along with identity resolution (described below) and omnichannel marketing, to reach the same audience on multiple devices with personalized messaging.
4. Identity Resolution for a 360-Degree Customer View
To offer the best omnichannel experience, you need to recognize and tie together your customers’ identities across all the channels and devices they use. Identity resolution helps you do that, enabling you to expand your view of a customer to their apps and interests.
Identity resolution makes possible more precise targeting, omnichannel tracking and measurement, and personalization at scale.
You can use a toolset such as StiristaLINK, which connects B2B and B2C identities for a 360-degree view of your prospects. This lets you develop integrated communications to reach the same person, for example, via Facebook, Twitter, other social channels, and personal and business email.
5. Artificial Intelligence and Machine Learning
Top data-driven marketing companies like Google, Facebook, Amazon, Twitter, and LinkedIn are already actively using artificial intelligence (AI), machine learning, big data and predictive analytics to improve their products.
For example, LinkedIn uses machine learning (the ability of machines to teach themselves from data they collect) to power its smart replies recommendation engine.
Google uses artificial intelligence and predictive analytics to power its autocomplete search prediction engine. Once you begin typing in the search box, an algorithm utilizes all user data acquired to show what you might be interested in before you finish typing. These predictions are based on information gathered on the interests of other people with similar search queries.
Google’s latest product release, RankBrain, uses predictive analytics and AI to decide which pages to rank in search results, in real time. It understands searchers’ queries (keywords), measures how people interact with the results (user satisfaction) and then ranks the pages that best answer users’ questions.
Facebook also uses machine learning to power its Website Conversion engine. For example, the tool can calculate your cost per purchase and estimated conversions after 50 conversions. The “machine” requires a certain number of conversions to learn and predict which type of audience will better respond to your offer in the future.
So, there you have it: Five crucial data-driven marketing trends to adopt or start using more extensively. Now more than ever, businesses must assemble and integrate customer data to gain insights that will help you create a great, seamless customer experience spanning multiple channels. Leveraging these trends will move you along that path toward better results.
Which other trends should be added to this list? Tell me about it in the comments.