Micro Moments: The Crown Jewel of the Customer Journey

Marketing trends and technology, particularly around mobile, are changing rapidly. And operating systems, devices and applications are being developed quickly. Apple’s recent announcements for its iPhone 6, iOS8, Apple Watch and Apple Pay are yet more evidence of the fast-paced growth in technological capabilities and the consumption of communication and media.

So how can mobile technologies and data help us to manage the customer journey, and engage the customer better? I recently wrote about mobile marketing comparing native mobile apps versus HTML 5, but this is so 2013!

Hence I feel the urge to write on how new technologies can help us engage our clients better. And no. I am not going to discuss social and / or advertising in this column.

So what we are really discussing here is geo-fencing, geo-targeting, usage of behavioral mobile analytics, and linking it to a data-driven multi-channel engagement lifecycle campaign. Sounds big, let’s break it down.

The title ‘micro moments’ suggests that attention spans from mobile consumers are short, and thus have to be characterized by short, actionable, timely communications and with relevant content. This in essence works by – you’ve guessed it right – triggers that are sensitive to location, to the usage and the situation the customer is in: making it all highly contextual.

Geo-fencing is a technology that allows the marketer to select a geographical point of where the user is, and surround them with a fence. If the user then crosses that boundary, they will receive a triggered notification (think altitude and longitude). We’re looking into one-to-one communication with the customer from a segmentation perspective.

Geo-location is the ability to target consumers based on their general location. This is a one-to-many communication from a segmentation perspective. While these technologies have been around for sometime now, marketers and vendors are improving their reach, the ability to collect data (A.K.A stalking!) in big data modules, and aggregate it in sophisticated modules that allow them to serve the customer with much more relevant communication that results in higher ROI.

Here is an example:

PerfectProduct is a ’bricks and clicks’ department store (physical shops and e-commerce) that sells online and offline and has branches in different states. Apart from transactional data (purchases), e-mail addresses, mobile phone numbers, and personal information, they also keep track of devices the user is using (via their installed app), their purchase habits per device, and the specific stores they visit (physical shops, and e-commerce).

PerfectProduct is also using a marketing platform that allows them to serve their customer via multichannel lifecycle tools.

The Story Begins

PerfectProduct has just started to promote its Christmas offerings across its shops and is currently e-mailing vouchers for various products to loyal clients for use online and in-store.

Jorge, one of their loyal customers has not used the voucher for four weeks now. By this point, Jorge according to the business’s eRFM model, is a churning Gold customer. We also know Jorge has downloaded, and is using the PerfectProduct application.

A Moment With Jorge

While Jorge was traveling to the next closest city with his family, all Gold churning customers in the area of the city who have not used the voucher, receive an SMS (geo-targeting) and are told that they are close to a PerfectProduct shop (with a link to Google maps) and that their voucher will expire after the weekend.

Micro Moments In Action

As Jorge and his family walk into the first level of the shop, Jorge receives specific offers by email for children’s clothing, available on this floor, and by the time they have walked up to the second floor specializing in women products, Jorge has decided to open the PerfectProduct app and a push notification alerting him of the newest collections of handbags, including discounts for Gold customers.

To make sure it is sending the right offers, PerfectProduct supports the data accuracy of its offering with iBeacon. When Jorge entered the store, several strangers also entered the shop in response to the push notification announcing the handbag sale on the second floor. Because the PerfectProduct database contains the unique identifier of Jorge (e-mail address in this case – other identifiers can be considered), instead of being an anonymous visitor, PerfectProduct can treat Jorge in the right context and drive him to the right content based on his historical purchase, and current situation.

Customers who didn’t have the app were sent downloadable vouchers to their Apple Passbook or Google Wallet which could be triggered via location-sensitive communication.

This journey can continue if Jorge doesn’t purchase in the shop, and we can look into retargeting Jorge in case he did not buy anything.

Minority report? Not necessarily. The key to bringing it to reality is to collect data, score clients, and link channels and customer behavior.

Until next time, stay tuned!

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