How Data and Machine Learning Can Help You Run More Effective Ads
A guest article by Pollen, a highly automated marketing platform available for use by nearly every eCommerce business out there. The app simplifies online advertising and takes the burden of creating a campaign strategy, testing, and optimizing of the user and relies on data and its powerful machine learning technology to drive sales.
The most valuable commodity to any growing online business is eyeballs. In other words, how can a small retailer compete with the deep pockets and vast resources of larger brands for customers’ attention? Does the little guy have a chance anymore?
Generating qualified traffic is certainly not easy. In fact, according to Hubspot, nearly 63% of companies report that new customer acquisition is their top marketing challenge. Creating a healthy funnel of steady traffic can not only seem difficult but often times impossible. And, converting that traffic from interested shoppers to paying customers is even harder.
One way small eCommerce retailers can compete for attention with large companies is by leveraging the power of machine learning technology to serve more effective ads. While that may sound a lot easier said than done, it is possible, and it does not need to be the least bit complicated.
Using Data To Drive Sales
The concept behind machine learning is creating programs that learn without being explicitly told what to do. Traditionally this has been a pursuit reserved for brands with huge discretionary budgets. However, lately, there are a ton of incredible companies releasing tools to the masses built on machine learning and artificial intelligence. From x.ai a robot-assistant built on machine learning to Eloquent, which helps you answer common customer service questions using AI, there are a lot of companies using serious data science to address big issues.
In advertising, there is little time for guesswork. Most small businesses don’t have enough capital to properly test their campaigns or the know-how to use their data properly. This is why Pollen uses machine learning to help you run ad campaigns that get smarter and perform better over time and the core of this is based on your own data.
There is a lot of data available on the internet, but what type is valuable to a business trying to generate new sales?
The best place to look first is current customer data. Current customer data can tell a business a lot about who to target next. This includes demographics, transactional history, social engagement, and email subscriber lists. The good news for SMBs is that Facebook allows access to infinite demographic segmenting across its 1.28 billion daily active users.
The concept here is that since a business’s current customer list purchased its products, shouldn’t people similar to its current customers also be interested in those products? With this type of data, online retailers can understand common threads among its customers, identify and create lookalike audiences, and serve those new segments ads to generate relevant new traffic.
The process of harvesting data and serving ads to new audiences sounds complicated and time-consuming, but it does not have to be. By leveraging machine learning technology, online retailers can automate the entire acquisition stage of the marketing funnel so they have time to take care of other matters.
Retargeting To Increase Conversions
It is important to note that 92% of consumers do not visit a site for the first time with the intent to purchase. Shoppers tend to want to do some research, especially before they make bigger purchases. In order to keep a brand top of mind, retargeting becomes a highly influential tool for increasing conversion rates.
While many might be skeptical of retargeting, it is actually a highly effective tool for boosting conversion rates. This strategy can increase ad response by up to 400% and according to CMO.com, online shoppers retargeted with display ads are 70 times more likely to convert. Without any extra effort from the user, Pollen can create unique targeting strategies by serving dynamic and static retargeting ads on Facebook and across millions of websites.
Growing businesses need to make decisions based on data, not on a hunch or a gut feeling. Guesswork can leave money on the table. A/B testing is a surefire way for any business to determine the effectiveness of certain elements of a campaign, but that takes time and effort that many small businesses don’t have.
Another question SMBs may run into is how to determine how much budget to allocate between prospecting and retargeting. The answer: artificial intelligence can optimize budgets to ensure each store successfully drives users through their funnels. Ultimately, using data to make sure SMBs are not leaving money on the table.
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