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.

Keeping it light today

A little bit of trivia: Did you realize that this year, the iTunes Store became the #1 seller of music in the United States? Over 5 billion songs have been downloaded from the iTunes site since it's inception in 2003.

Those are a lot of $0.99 plays. Is the compact disc format on its way out?

http://en.wikipedia.org/wiki/Itunes_store

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.

The tangled web of marketing

Remember 30 years ago, when a brand manager would have the following (perhaps a few more, but these are the main) options available to him or her?
- Television ad spots
- Radio ad spots
- Newspaper and Magazine advertisements
- Trade promotion dollars for endcap displays

Fast forward to today: Retailers have more power in the negotiating process than ever before, slick technologies like TiVO, the web, etc. are reducing (or possibly eliminating) the influence of commercials and print advertisements, and there are more and more devices out in the market by which marketers have options to position their products today.

Add to that, the ever-increasing influence of the online space... which has been growing double digits for many years and is pulling more and more ad dollars away from traditional media. The good news is that the web offers advertisers and merchandisers new means to market to, especially younger, consumers. Better yet, the web offers what traditional ad spots have not really been able to definitively provide, quantifiable metric-gathering ability by which to measure the Return on Marketing Investment... which in a world where marketing (and all expenses for that matter) is being increasingly scrutinized is a really good thing.

However, the not-so-good news is that the web, and especially now the emergence of Web 2.0, provides an increasingly complex number and types of channels available to use in the marketing mix. Paid search, unpaid search, website impressions, click-through advertising, email, affiliate marketing, social commerce, social networking, SEM, cell phone couponing... you get the picture. And I'm sure that there are more options than that. With options, of course, comes the risk of analysis paralysis... "Which options should I use?" "What's the latest 'new' thing?" "What am I getting out of this ad, really?"

In reality, depending on your target segments and the types of behaviors/actions you want to influence, any one or a combination of these tools may be used. I will not go into any one of these right now (that would be for future blogs, of course), but here are my thoughts about evaluating your mix:

- Who are your customers? And how do they interact with you and others online?
- What is your desired outcome? Is it awareness? Visiting your website? Creating UCG to support your brand? Sales (obviously everyone's endgame)?
- What tools provide the most logical resource to accomplish your desired outcome and can the technologies/partners you use provide accurate and actionable measurements to help you assess your Return on Marketing Investment?
- How do these online channels interact with your current offline channels? Can you leverage cross-channel marketing?
- Do you have the right data on your customers (behavior, preferences, history, etc.) and sufficiently robust analytics available to make intelligent decisions about targeting with these channels?
- How rapidly can you adjust your messenging/strategy using this means if there is a need to course correct?

These are my initial thoughts. I will provide thought on specific tools later.