How cloud computing is accelerating contextual advertising
Retailers and marketers often face the challenge of getting coupons, offers and promotions delivered at the perfect time and in the right context to their customers.
The rapid advances in cyber foraging, contextual computing and cloud computing platforms are succeeding at revolutionising this aspect of the retail shopping experience. Context-aware advertising platforms and strategies can also provide precise audience and segment-based messaging directly to customers while they are in the store or retail outlet.
What makes context-aware advertising so unique and well adapted to the cloud is the real-time data integration and contextual intelligence they use for tailoring and transmitting offers to customers.
When a customer opts in to a retailer's contextually-based advertising system, they are periodically sent alerts, coupons, and offers on products of interest once they are in or near the store. Real-time offer engines choose which alerts, coupons or offers to send, when, and in which context.
Cloud-based analytics and predictive modeling applications will be used for further fine-tuning of alerts, coupons and offers as well. The ROI of each campaign, even to a very specific audience, will be measurable. Companies investing in cloud-based contextual advertising systems include Apple, Google, Greystripe, Jumptap, Microsoft, Millennial Media, Velti and Yahoo.
Exploring the framework of "Me Marketing" and context-aware offers
A few years ago, a student in one of my MBA courses in international marketing did their dissertation on cyber foraging and contextual mobile applications’ potential use for streamlining business travel throughout Europe.
As a network engineer for Cisco at the time, he viewed the world very systemically; instead of getting frustrated with long waits he would dissect the problem and look at the challenges from a system-centric view. The result was a great dissertation on cyber foraging and the potential use of near field communications (NFC) and radio frequency identification (RFID) as sensors to define contextual location and make business travel easier. One of the greatest benefits of teaching, even part-time, is the opportunity to learn so much from students.
I’ve been following this area since, and when Gartner published Me Marketing: Get Ready for the Promise of Real-Time, Context-Aware Offers in Consumer Goods this month I immediately read it. Gartner is defining Me Marketing as real-time, context-aware offers in grocery stores.
Given the abundance of data on transactions that occur in grocery stores, Gartner is predicting this will be the most popular and fastest-growing area of context-aware offers. The formula for Me Marketing is shown below:
The four steps of the Me Marketing formula are briefly described as follows:
- Consumer insight and permission - The first step of the framework and the most difficult from a change management standpoint, this requires customers to opt in to receiving alerts, coupons, offers and promotions. The best retailers also have invested heavily in security and authentication technologies here too.
- Delivery mechanism and in-the-moment context – The real-time offer engine is used to determining which coupons, offers and promotions are best suited for a specific customer based on their shopping patterns, preferences and locations.
- Select best offer – Next, the real-time offer engine next defines a very specific product or service offer based on location, previous purchase history, social media analysis, predictive and behavioral analysis, and previous learned patterns of purchasing.
- Redemption – The purchase of the item offered. Initial pilots have shown that less frequent yet highly relevant, targeted offers have a higher redemption rate. It is encouraging to see that early tests of these systems show that spamming customers leads to immediate opt-outs and in some cases shopping competitors.
A short overview of contextual advertising and the cloud
Cloud-based systems and applications are necessary for retailers to gain the full value that contextual advertising can provide.
This includes the social context, with specific focus on aggregation and analysis of social CRM, CRM, and social media content, in addition to behavioral analytics and sentiment analysis. It also includes the previous browsing, purchasing, returns and prices paid by product for each customer.
Cloud-based integration architectures are necessary for making contextual advertising a reality in several hundred or even thousands of retail stores at the same time.
Geographical data and analysis is also essential. RFID has often been included in cyber foraging and contextual advertising pilots, in addition to NFC.
As GPS (global positioning system) chip sets have dropped in price and become more accurate, companies including Google, Microsoft and Yahoo are basing their contextual advertising platforms on them. Finally the activity or task also needs to have a contextual definition.
Combining all three of these elements gives the context of the customer in the retail store. The figure below is from Three-Dimensional Context-Aware Tailoring of Information. This study also took into account how personas are used by companies building cloud-based contextual advertising systems. The taxonomies shown in the figure are used for building personas of customers.
There are many pilot projects and enterprise-wide system tests going on right now in the area of cloud-based contextual advertising. One of the more interesting is an application suite created entirely on Google App Engine, Android, and Cloud Services.
The pilot is explained in the study Exploring Solutions for Mobile Companionship: A Design Research Approach to Context-Aware Management. The following figure shows a diagram of the suite. This pilot uses Cloud to Device Messaging (C2DM) which is part of the Android API to link the Google App Engine server and Android client. Google will most likely add more depth of support for C2DM as it plays a critical role in contextual system development.
Benefits of a cloud-based contextual advertising platform
For the customer, cloud-based advertising systems over time will learn their preferences and eventually impact the demand planning and forecasting systems of retailers. This translates into the customer-centric benefits of products being out of stock less.
In addition, customers will receive more relevant offers. The entire shopping experience will be more pleasant with expectations being met more often.
For the retailer, better management of product categories and more effective gross margin growth will be possible. Having real-time analytics of each coupon, offer and promotion will also give them immediate insights into which of their selling strategies are working or not.
For the manufacturer, the opportunity to finally understand how customers respond at the store level to promotions, programs including the results of co-op funds investment and pricing strategies will be known. The manufacturers who partner with retailers using these systems will also have the chance at attaining greater product differentiation as their coupons, offers and promotions will only go to the most relevant customers.
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