In earlier times, marketers (like me) regularly utilized data that was outdated, incomplete, erroneous, and statistically insignificant, to make daily decisions about how we were going to improve our marketing effectiveness. Only some activities were trackable. Reporting required ad-hoc data dumps and requests from IT. We used Excel, a lot. We struggled to determine cause and effect of each activity/result. Connecting the dots was full of assumptions and guesswork. And just as we began to understand why something was working, or failing, our priorities changed. We simply didn’t have practical ways of understanding how any particular marketing effort influences, or is influenced by, whatever else was happening in the customers’ journeys. The norm was that you treated each marketing effort as an independent effort. Well, that was then.
And, it’s still what most marketers are doing today!
It’s true. Yes, there is A/B testing for improving isolated components. But from a broader perspective, the average marketer doesn’t have the time, budget, resources, nor expertise to make that pay off. And most advanced analytics offerings are not marketing-friendly. Instead, marketers must quickly and regularly monitor and collect performance data, make conclusions, adapt the messaging, targeting, and balance of resources. Then they update setting in their campaign systems (digital or physical) and keep going.
The average marketer has to quickly roll out campaigns such as:
- customer events
- new product line
- new store
- holiday sale
- loyalty program
- social campaign
As campaign components roll out, understanding their performance in context to each other can be impossibly complex, especially when you consider that the marketer often hits the same customer through many channels (the “omni-channel” shopper), such as web ads, TV, email, text, apps, mobile, in store and POS interactions, etc.). And on top of that, every shopper/human is different by nature. Finally, even if the marketer could understand who, what, when, where, why, and how, they are still faced with the task of… “So how do I do it better now?”
The marketer’s only choice is to use a flawed toolset for making decisions about how to optimize the customer journeys and promote revenue growth. Those tools include: gut feelings, common sense, intuition, witchcraft, opinions, assumptions and voodoo.
As of late, marketing automation tools have provided massive benefits and efficiencies in developing and delivering complex, segment-based multi-stage, multi-channel campaigns, including Marketo, Eloqua, HubSpot and others. And linkage with CRMs and databases support those systems and provide important feedback loops.
The gap is in the middle – the need to create and deliver analytic-driven recommendations to the campaign management systems.
These recommendations must be timely, personalized, and in context to the shopper’s goals, buying stage, and history (his journey).
Organizations are starting to understand the benefits of real-time customer engagement and journey management. Several technology breakthroughs, such as: Real-time analytics, IoT sensors, beacons, Data lakes / Hadoop, Data Bases / Customer Data Platforms (CDP), marketing automation platforms) have enabled the potential for marketers to catch up to their customers in real time, and actively prescribe personalized recommendations, on the right channel and at the moments. And keep doing it, in an automated fashion.
Some marketers are using these to build customer personas and segment their data bases for complex campaigns. And while these capabilities are critical for journey management, these CDPs and marketing automation tools don’t “do” journey management. Journey management is the gap in many marketers’ tool kits.
Instead, most marketers are still using gut feelings, common sense, intuition, and opinions, and voodoo, in a reactive and siloed decision management mode for executing campaigns. Journey management, done right, means that marketers can easily surface goal-based intelligence about what actions and offers should be delivered to whom, in what way, at what time. And these insights are in context to the individual shopper’s persona and their actions. And those recommendations are seamlessly channeled to the marketing automation platform for execution.
And THAT, my marketing friends, covers the gap. Journey management is a relatively new field and most marketers don’t understand what they don’t have. They have data bases, they have a way to create a persona and make a segmented list, but they can’t connect the analytic dots to know what to do “now” and disseminate the next best actions across their campaign components. Journey management, done right, makes your marketing automation “smart”.
As consumers, we understand what “smart” marketing is. It’s when we feel that we’re being led on a journey that we didn’t even know we wanted to take. Instead of buying a product, we have highly personalized interactions and engage in a more holistic brand experience. And we become more loyal and… we buy more stuff.
One such solution for marketers who want to improve customer engagement in this way, is TCS Customer Intelligence & Insights, from TCS Digital Software & Solutions Group. It was recently named Best in Class in Customer Data Aggregation, Analysis and Segmentation, Customer Journey, and Integration Capabilities by EnsembleIQ Research, with details in this announcement.
The market for journey management, and customer engagement solutions is on the rise. Marketers will increasingly feel that they are in the stone age without them. It’s critical that marketers do not make the mistake of assuming that that they already have the capability.