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Why data science must stand at the forefront of customer acquisition

Though flashy advertising campaigns tend to get most of the attention, in reality, data science is what will ultimately have the biggest impact in ensuring effective customer acquisition.

Just how valuable can big data be for a business? Some analysts believe that simply increasing data accessibility by 10 percent can help the average Fortune 1000 company generate an additional $65 million in income.

Quality data can be even more valuable for new startups. When you have a limited marketing budget, you can’t afford to let your customer acquisition efforts go to waste — especially when in many industries, companies spend hundreds of dollars to acquire a single customer.

Unlocking the potential of data science and analytics will enable you to gain greater insights into your customers, allowing you to spend your marketing budget more efficiently. Here are some of the top reasons why data science should play a central role in your acquisition strategy.

Identifying signals of intent and creating predictive models

When it comes to making the most of your marketing budget, few insights are more valuable than discovering why a customer wants to buy a particular product or service. This intent is usually signaled through a wide range of resources, including Google searches, visiting shopping comparison sites or reading product reviews on your own website.

Big data helps identify when a particular user is engaging in these activities, indicating that they are more likely to become a paying customer with the right marketing push. Targeting the right person at the right time is usually a recipe for sales success. Over time, as data science determines the strongest signals of intent, your team will also be able to create predictive models that will allow you to consistently target those who are most likely to convert.

By focusing your customer acquisition efforts on the customers that are demonstrating signals of intent, you’ll be able to stretch your advertising dollars further and get a much greater return on investment. Analytics can even be used to predict future needs, allowing you to nudge current customers at the right time to encourage additional purchases.

Testing marketing strategies

Data doesn’t just help you identify those who are most likely to make a purchase; it can also help you fine-tune the strategies you use to guide potential customers through the buyer’s journey. A/B testing can be used to determine the effectiveness of everything involved in customer acquisition. From comparing email campaign copy to changing the location of your call-to-action button, these tests will enable your team to find ways to keep customers engaged until they make a purchase.

As an example of this, Google Analytics allows businesses to break down their e-commerce products based on product list performance. This data goes well beyond revealing how well a certain item sold. It can also reveal which items receive a lot of views, but few clicks, or even which items are most likely to be abandoned in a consumer shopping cart.

Identifying underperforming product lists can greatly improve your customer acquisition efforts. Data will help your team find the reasons why a particular product isn’t performing well, or help you decide to discontinue an unappealing product. In some cases, even something as simple as changing the display order can provide a boost in sales — and A/B testing will reveal the answers.

Improved segmentation yields improved targeting

Not all customers are created equal — while some may become lifelong devotees to your brand, others may only make a single purchase. A customer may not generate a profit from an initial purchase, but if their lifetime value outweighs the cost of acquisition, your company will be better poised for long-term success. Once again, proper use of data analytics can help you identify the right customers to target as part of your acquisition strategy.

The Lyric Opera of Chicago “used machine learning algorithms to take into account hundreds of dimensions at once” to better fine-tune their audience segmentation strategy. Even without predictive modeling, these algorithms examined a wide swath of data that described top opera-goers. Combining this data with lookalike modeling improved their conversion rate by 3.7 times with a high-value group.

Segmentation data will allow you to identify those individuals who deliver the highest average customer lifetime value, ensuring that those you reach with your customer acquisition efforts will deliver significant profits in the long run.

The potential of big data

Put simply, better data enables better decision-making. Leveraging the power of big data will do much more than help your marketing team create more effective advertising campaigns. It can help you adapt your web content, fine-tune your SEO efforts and even help you discover new potential customer groups, all by providing invaluable insights that you wouldn’t be able to discover on your own.

For companies that truly wish to maximize their potential for customer acquisition, it is clear that big data is the key to a successful future.

InnoValeur | Data Science | Smart Data | Machine Learning | AI

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