Irony: Optimizing Marketing Automation Requires Human Intervention

It seems to be a great truth in digital marketing that the more automation you apply to data management, the more you need smart people to manage and optimize it. Contrary to the machine automation benefits of the 20th century, where automation on the assembly line increased productivity and replaced human workers, marketing automation technology increases output efficiency and scale, but still requires marketing expertise and analytics to ensure the ROI. Think about it. It’s not a failure of technology or faulty logic. I believe it’s simply good business strategy.

Will the marketer not bogged down in operational details and with plenty of time for strategic planning please step forward? Yes, that would be a lonely line I suspect. We crave the benefits of marketing automation because we want to automate the execution of campaigns. However, we can’t automate the strategy. No technology in the world can understand the nuance of customer behavior for our business, create compelling creative assets, and ensure that the analysis and analytics we perform as meeting the right benchmarks for ROI. The results of our automation certainly give us guidance and can generate data – and make it accessible for insights – like never before. But technology doesn’t come up with great creative approaches and associate the right message with the right lifecycle stage. Humans do that. Analytic, customer-centric, marketing-savvy, and digital-experienced humans, to be specific.

It’s sort of like the old maxim about the art and science of marketing. The art is done by humans, the science by technology. It’s helpful to think of the co-dependency that way, even though the lines are somewhat porous between them. The reasons that marketers invest in marketing automation technology are usually tied to two main goals: data integration and accessibility, and productivity and efficiency. That includes both art and science benefits. Some of the problems that automation technology solves include:

  • Improving marketing efficiency:
    • Obtaining a single version of the marketing truth to enable decision-making.
    • Understanding and improving cost savings on managing vendors, cross-database queries, and APIs.
    • Optimizing investment across channels. How much did customers buy at each stage of the journey? What is the purchase volume per impression?
    • Creating one set of measurable metrics.
    • Managing programs that involve one or more agencies and several internal teams (usually called “workflow” in technology offerings).
    • Ensuring cost savings – targeted impression-buying for equal or lower cost.
  • Data integration and accessibility:
    • Moving from basic customization of email to higher relevancy and targeting.
    • Creating advanced segmentation.
    • Having the ability to manage and optimize multi-touch nurturing campaigns.
    • Increasing programmatic buying and decision-making in real time.
    • Doing (or increasing) customer-level or persona-level analysis.
    • Taking advantage of digital consumer interactions – quickly, or in real time – across channels like email, web, call center, and social.
    • Utilizing anonymous (e.g., visitor) data to improve web and messaging experiences.
    • Enabling a complete view of the customer path to purchase (and repeat purchase).
    • Eliminating silos or marketing data.
    • Utilizing all or most of the data that is held on customers and prospects (across channels).
    • Tracking all visitor and customer touch points across channels.
    • Presenting the best offer for each touch point or lifecycle stage – both push (email) and pull (website or call center).

All those things are possible to achieve with good marketing automation or integrated marketing management tools. For example, we would know that this customer has come to X websites, participated in Y social communities, and registered for Z products – the technology tells us that. The technology can also determine the best offer to put in front of that customer, based on past purchase, season, and popular behavior. The technology can also tell us which channel to use to optimize response for this type of offer for this customer’s preferences. Propensity modeling can show us when to expect this customer to return, and what they may be looking for at that next visit. The technology can also predict the right times and offers for offline media that influences digital behavior – like broadcast and direct mail.

The human brain comes in when you start to consider the customer experience and journey. Humans ensure creative assets are in place and in the correct format – at every stage of this multi-channel journey. Usually more creative assets are needed the more customization the marketer enables via the technology. Analysts review the right reports, and discard unhelpful or outlying data in order to focus the team (and the budget) on the most successful offers, channels, and media. And, every customer interaction creates a new data point for future opportunity. The technology reports it all to us and executes our plans. But it doesn’t do the art – which is truly what makes marketing effective and powerful.

How are you managing the art and science of marketing, using the automation tools you have today? Are there gaps that technology can fill for you – in order to enable more strategic use of your human talent? Let us know in the comments section below.

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