The Non-Linearity of Buyer's Journeys

The future of digital marketing isn’t about creating funnels anymore. Funnels ‘leak’. They can be challenging to instrument, challenging to update and arguably even more challenging to update with real-time data for most companies. Using machine learning (ML) and artificial intelligence (AI) can empower marketing teams and their agency partners to harness insights derived from a? full gamut of internally and externally sourced data points.?

Teams can analyze prospective buyers in real-time, performing as a catalyst to deliver experiences that meet each of their individual needs at each stage of their individual journeys. From this analysis marketers can re-evaluate what works and what doesn’t on an ongoing basis.

After all, it isn’t about using the same tactics over and over again with the hope of achieving better results next time. It’s about capitalizing on the capabilities that these new technologies bring to the table that allow you to gain an intimate understanding of your buyers ‘in the wild’ and the effectiveness of your marketing investments.??

Buyer’s Journeys Aren’t Straight Lines - A buyer's journey is an interconnected series of stages. These stages help marketers to observe progress as target audiences, personas, companies or individuals meander through sea of content and opportunities to engage with your brand’s messaging across multiple channels.? Ultimately, those persons are seeking an answer to a question or a solution to a pain which they are experiencing. Marketers will tell you, broadly speaking, that the stages reflect progress from awareness to conversion.?

The vast majority of people don’t intentionally learn about a product, service or solution by following a linear path that a marketing team or agency outlines. They do what they want, when they want with individual motivations for making progress in a timeline which they need to be successful. In turn, people (a.k.a. buyers) could end up anywhere at any time during their unique journey. Starting in the middle, the end, or revisiting stages over and over again can wreck havoc on a marketer’s data and understanding of what’s working and what isn’t. Today’s marketing capabilities generate enormous amounts of data to sift through. Therefore, the?equivalent of a three-dimensional, parallel universe model of a buyer’s progress is needed to help marketers to market more effectively.? And this is where ML and AI and corollary data visualizations and help.?

They can let you see multiple journeys taking place at once, quickly inform real-time adjustments to paid media channel selection and spend, ascertain content performance, CTAs, inform your content strategy, competitive inroads and more. This is not easy mind you, but necessary to be as efficient and effective as possible with your financial and human resource investments especially at scale.?

People Don’t Fit Inside a Funnel - The problem with a traditional funnel are the people you are trying to reach. A funnel implies large audiences head in a straight line downward by neatly dropping in at the top after catching them with a large marketing net, a subset is wowed enough to move further downward and the strongest survivors fall out the bottom ready to buy.?

Can you reflect the progress your team’s investments have made or understand how your content and messaging is performing in a two-dimensional, ridgid funnel if your target audience is moving left, right, up, down? You can derive some insights and look at the high level results.? But you won’t see what tactics or investments could have been further refined until your campaign is already complete. Useful?? Sure. Could it have been more useful to adjust course and speed while the campaign was live? Definitely.?

This lost potential and holes in the data are often referred to as ‘data leaks’. Like most leaks, left unchecked they can cause damage and this case the damage is to your marketing’s efficiencies. Consider the outcomes if a prospective buyer receives irrelevant or insufficient information about your products and services at the time and place that they need it. They may get lost, develop a negative impression about your brand or worse, drop their pursuit of knowledge and move on to another company.

Drive?- The linearity of traditional marketing funnel analytics doesn't offer the insights a modern marketing team needs to successful over the long run. In an effort to understand how best to use ML and AI for performance attribution, focus on understanding how people interact with your marketing tactics throughout their individual journey. Continually align this understanding to your campaign’s goals and objectives.

A more fluid, non-linear and almost topographical data visualization model endowed by AI and ML capabilities is an effective, and for many, aspirational method to a greater understanding of?audience journeys. Done well, the opportunity to drive your marketing scale and improve the yield of your investments is within reach. And with the current economic headwinds, who doesn’t need to improve their team’s efficiencies and yield?