The sales funnel is a common data visualization model that describes the progression of customers from the discovery and awareness of a brand or business through to consideration and eventually sales and repeat sales.
The sales funnel has become largely digitized in recent years. It used to be a much more primitive model, especially in the pre-internet era where marketing and sales were telephone-based or face-to-face.
Today, the digital sales funnel creates opportunities to utilize data to optimize the sales and marketing process.
These tips are angled at start-ups and small business operators and be implemented by pretty much anyone, regardless of their experience in data.
As well as understanding how the sales funnel works (see below), if they haven’t already, small business owners should set up Google Analytics on their websites. It’s free, easy to use, and enables tracking of all key (and many advanced) website metrics. Google Analytics is a free data platform designed to track website metrics and other user and traffic KPIs.
In addition to Google Analytics, the native data tools integrated into social media platforms also provide lots of useful information that can be used to optimize sales funnels. Aggregating data across all business touchpoints is possible using a customer data platform which is a SaaS software class purpose-built for this job.
The Sales Funnel
Discovery and awareness are tied closely together. Both measure how many new individuals are discovering your business. Think With Google says that some 87% of online purchasing journeys start with an internet search. It’s a similar story in B2B too.
As such, organic search is paramount, which makes having a content marketing strategy essential. Whilst the website blog is the staple of content marketing, it needs to be backed up by social media content. Here are some excellent social media tips and tricks that you can use to build inbound marketing growth.
In terms of the data, the metrics you want to look at here for stage 1 of the funnel are:
Website visitors can be tracked in Google Analytics under Audience > Behavior > New vs Returning. What you’re ideally looking for here is a climb in new users once you launch a content marketing campaign aimed at boosting discovery, e.g. a series of blog posts with accompanying social media posts.
Useful content here includes news and thought leadership from within your industry, blog posts, and articles aimed at providing values and trending topical discussions. On the social media side of things, giveaways and competitions are an excellent way of building brand discovery.
Google Analytics also lets you explore your user’s demographics, interests, location, and more.
This allows you to get a better picture of who your customer personas are, thus allowing you to tweak content to your actual audience rather than your expected audience. Social media data tools have similar features that allow you to delve into your user’s demographic data.
Interest and consideration are harder to measure, especially in B2C where you’re looking at potentially large volumes of data compared to B2B where you might be focussing on just a handful of leads.
One metric to look for is an increase in returning users. Increases in new users show that inbound marketing techniques are working, but increasing repeat users shows that some of these new users are sticking to your site and social accounts, consuming content on a regular basis.
Additionally, by tracking the percentages of users that are heading to your product pages specifically, you can get a feeling of how many users are interested in your products.
Nurturing potentially interested users is about timing promotions to nudge them towards your products. Tracking pixels can help businesses pick up on who these users are and target them with remarketing ads offering promos, discounts, etc. In B2B, users dwelling in your products and content without taking action are worth reaching out to with outbound marketing.
If your data suggests that your total users are shifting from new to repeat users then this might be an indication to switch your entire content networking to something geared more towards your products.
Converting sales requires a little more squeeze. Fostering purchasing intent builds upon the campaigns set out in stage 2; use promos, discounts, and other sales tactics.
Conversions can be optimized by tweaking product pages, landing pages, and the checkout process. A/B testing is important when it comes to checkout, landing page, and product page optimization and can be implemented with Google Analytics.
Conversion optimization is about making the purchasing process very easy and friction-free. Email, pop-up, and notification reminders e.g. “we noticed you’ve left some products in your cart” can help prevent cart abandonment.
Look for potential errors in your checkout pages – they need to be clean and error-free with a variety of payment options. Use your data to correlate sales with actions further down in the sales channel.
These are just the basics of building a data-driven sales funnel that uses empirical measures combined with some manual market research. Google Analytics does a good job of basic funnel and customer data analysis but you’ll probably want to look into customer data platforms (CDPs) at some point.
CDPs aggregate user and customer data from multiple touchpoints and enable it to be piped to everything from recommendations and remarketing engines to business intelligence tools and more.
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