Self-Service and Real-Time Analytics

As I had written before, the consumer-facing market is migrating into more and more of a self-service model with the prevelent use of ATMs in banking, self-checkout and self-ordering devices in Retail and Hospitality, and the growth of eCommerce online merchants. This channel obviously provides the consumer and the merchant with some advantages (convienence, efficiency, etc.) but it has one notable disadvantage. This disadvantage is obviously the lack of person-to-person interaction in these exchanges. In such an environment, how does the consumer feel that she is "known" and the merchant able to conversely "know" the consumer?

In businesses where self-service works well, the merchant has to "know" the consumer based on her previous interactions with the company. What are her tendancies, history, affinities, etc? Based on the occasion that she is shopping within, what type of merchant offers will be relevant to her? This type of knowledge requires "real time analytics" in the sense that the shopper's behavior is analyzed and her tendancies are known... and then based on the predicted shopping occasion (fill-in, splurge, pantry filling, convienence trip, etc.) can the merchant offer her an incentive to make that visit more profitable for the merchant and more valuable for the consumer?

Obviously, in the eCommerce world the merchant will know through the contents of the consumers' shopping basket and her session clickstream behavior. Is this possible in a brick and mortar world? Is it possible without real-time basket information? Possibly... but this would require that the shopping and occasion data is available and the patterns are analyzed on every customer... something that requires sophisticated analytical CRM tools and an active data warehouse environment with the horsepower to support it (obviously the merchant needs to know in some way when the consumer is interacting with them). In the banking world, this can effectively be handled through the ATM device similarly to the way Amazon would offer a next best offer from a purchase.

However, what would the ROI on consumer marketing efforts be if, like eCommerce, you could analyze and dynamically offer value-added services in the midst of the shopping occassion... at the point of purchase instead of the point of sale? There are some mechanisms for doing that today, but they are by no means segemented. There is one retailer that is experimenting with self-scanning technology within the store... if this could be married to the offer and relationship management technology it could be a huge win for them, both in terms of understanding their shoppers but also in marketing effectively to them on their terms.

The Analytics ROI Question: "Which came first, the chicken or the egg?"

Everyone has likely heard the riddle: Which came first, the chicken or the egg? I do not know what the answer to that question is, and perhaps it is more a philosophical one to assess a person's position on origins...

Having spent a signifiant part of my life in the business development world in the Enterprise Data Warehousing market over the past couple of years, the question is also generally heard but in a different form: "Who takes credit for the ROI on my Business Intelligence project, the data warehouse infrastructure or the analytics/applications that make sense of all of this data?" In the sales world, this is an important question because it determines the strategic importance of a vendor's products. Of course, that strategic importance ultimately determines the vendors' share of wallet with that company and over the long term in the industry. Money talks. Therefore, like a good politician every technology is out there to take credit for the analytical ROI.

For an analytics or application solution like SAS, Retek, Siebel, TRM, i2, SPSS, Microsoft analysis tools, etc... the value is obvious. The deep analytics and decision-making capabilities enable companies to drive to decisions and answers they were not able to reach prior to having those tools and applications in place. Without the decision-making intelligence, no decision, no benefit, no ROI.

However, the database and infrastructure vendors also have a case to be made... especially the MPP (Massively Parallel Processing) database technology vendors like Teradata, DATAllegro, and Netezza. Without the ability that the database engines provide to crunch through terabytes worth of detailed data at the atomic level, the analytics engines that depend on this machinery would not be as effective. Therefore, they may say: "Not too fast, you're delivering that value on our nickel. We should take credit here."

Interestingly enough, only recently the BI market was relatively fragmented. Application vendors, BI vendors (Cognos, Business Objects, Hyperion, Microstrategy, etc.), and the database infrastructure vendors (Oracle, Teradata, IBM, etc.) were all in their own camps. And as such, each vendor sold on the merits of their own tools in this interdependent technical environment. Today, the industry is starting to consolidate where BI and application companies are being bought up by larger infrastructure players (IBM, Oracle, and SAP... who is taking the analytical market more seriously now). As such, it is now possible for a company to get all of their analytical needs met by a single vendor and gain a complete picture of the benefits and returns without necessarily having to ration the cost/benefit among tools offered by different vendors. Of course, this is being said as the ROI evaluation process provided by technology vendors is, at the end of the day, a marketing and sales function rather than a consulting or financial evaluation function. In this world, having a vendor that can offer a single package that will deliver all of the goods will be to your benefit.

However, while there is consolidation in the market, all of the tools are (as far as I know) compatible with all of the major infrastructure platforms. Additionally, the deep analytics powerhouses remain independent (I'm thinking of SAS here) so there will be tension in the ROI credit discussion. Yes, even with all of the consolidation this is a very competitive market... especially with the DWA (data warehouse appliance) significantly lowering the cost for performance for infrastructure which is a great thing for IT staffs with limited budgets.

For an industry poised for growth, and a market ready to leverage those capabiliites, that is a good thing.