The sales funnel a ubiquitous data visualization model that maps the individual’s journey from discovering a brand to awareness, consideration, and ultimately, sales.
The primordial pre-internet sales funnel was fairly barebones and basic, likely involving some cold calling, face-to-face networking, pitching, and sales. Today, the sales funnel is almost entirely digitized.
Today’s digitized sales funnel ensures the presence of data – collecting, analyzing, and using customer data and behavioral data helps businesses optimize their entire sales funnel.
Discovery and Awareness Stage
Today’s potential customers mainly discover brands online – 87% of online shopping journeys begin with an internet search. In the B2B product research process, 89% of research processes use the internet. Most of the terms searchers use are generic, so researchers are looking for organic results.
This underlines that organic search rules the top of the funnel. In a B2C space, top-of-the-funnel marketing has a generally broad remit and includes content marketing and social media. B2B is similar but probably includes more outbound activity.
Locate User Demographics
The first sales funnel data to collect and analyze web traffic. This is also some of the simplest data to track, and Google Analytics provides the most required tools. The native data suites built into social media platforms are also pretty sophisticated.
Studying engagement demographics provides clues as to what type of people are looking through your posts and content – this is the first step to developing marketing personas. Look at age, gender, location, and other common attributes.
Changes in inbound traffic data can be tracked following content or social media marketing campaigns to discover what people are cottoning onto your content.
Interest and Consideration Stage
The interest and consideration stage is defined by leads who consume your content regularly across one or more channels. Comparing new users to existing users allows businesses to see how many existing users they’re retaining. High retention rates of existing users mean that pushing these repeat users toward products and sales could result in more conversions. The middle of the funnel is about fostering higher buying intent.
Time Your Campaigns
Google Analytics lets you compare new and existing users. Your unique user count should be high after building a campaign optimized for brand discovery.
Then, it’s about retaining the overall number of users while creating content geared towards fostering product interest and consideration, e.g., product guides, promotional content email offers, and adverts that offer purchasing incentives, e.g., discount coupons. Finally, use your data to identify when your new users are beginning to turn into repeat users – this is when to try and progress their position in the sales funnel.
Conversion Stage
High user counts but low conversion rates might indicate that your business fails to expose users to purchasing opportunities. They might be interested in your brand and what you have to say but aren’t interested in actually purchasing from you.
If your data tells you that this is the case (e.g., lots of return users but few sales), then ramp up a promotional marketing and remarketing efforts, creating buzz around product releases and exposing interested customers to that buzz.
Remarketing Pixels
Tracking pixels can help you target multi-channel adverts at customers who are most likely to convert. Once you capture an audience of interested users – users who regularly frequent your site and content – you can home in on them with product adverts.
The ‘marketing rule of 7‘ becomes useful here – people need to see your marketing messages seven times before buying. That means repeatedly targeting your repeat users with marketing efforts. Again, data helps you identify who your repeat users are in the first place and helps track how many times they’ve seen your content.
Retention Stage
Work is not finished when a customer purchases (particularly not in B2B). Optimizing the retention stage increases the total value of customers – or their customer lifetime value (CLV). Event data is extremely useful for identifying when and why customers leave a business, e.g., more people might leave at the end of the calendar month or when you fail to email them for a period of time.
Target Potential Churners
Reducing customer churn by targeting promos at the right intervals is possible. For example, you might find that customers that fail to buy from you again within a month after their first purchase leave for good. This indicates that targeting customers with promotional offers sometime before then increases their chance of making another purchase.
Qualitative data is invaluable here – use customer feedback and surveys to evaluate why customers leave your business, their pain points, and what you can do better.
Summary: Using Data to Optimize the Sales Funnel
This is just a small selection of ideas of how data can optimize the sales funnel. Instead of mulling over the “why did that happen?”, instead identify the data that will tell you why it happened.
Building a data-driven funnel will provide the small and precise insights that can lead to much larger results. It’s a problem-solving exercise that takes much of the guesswork out of sales and marketing.
