“Consumer marketing used to just be about ‘spray and pray’ tactics,” writes Hansen Lieu, a Director of Solution Marketing at SAP. “We looked at our consumer database and came up with our simple segments, from a combination of age, geography and race. It was an art not a science, often running on gut feeling and ‘experiences’. We all know the problems with this approach. It’s too generic and ineffective; and it’s entirely inside-out; you don’t get to draw on the customer’s preferences. Reaching your target buyers is a shot in the dark, requiring huge marketing budget and luck.” [“Targeting – the Marketing Game Has Changed,” The Customer Edge, 7 January 2014] Apparently, Lieu doesn’t believe in the power of prayer when it comes to marketing, or, maybe he just believes that prayer should be augmented by analytics. The opposite approach to “spray and pray” tactics involves specific targeting, based on data analysis, and is an outside-in activity. It’s called targeted marketing. Lieu concludes:

“Leveraging Big Data for targeting should be a key arsenal for marketers. Consumers have access to a lot of information, which enabl[es] them to change how and when they engage with brands and sellers. However, consumers also create and leave behind a long data trail. By leveraging real-time computing to process and analyze this data trail, marketers can also become more effective in how they engage and win customers.”

The objective of targeted marketing is the same goal of traditional marketing; namely, to close a sale and secure a profit. Ian Newcombe, Managing Director of Multi-Channel Solutions at Sanderson, notes that the new game played by consumers involves more retail channels than were used in the past. He writes, “Consumers demand personalised communications and offers from retailers, and multi-channel integration can make that expectation a reality.” [“Marketing automation + multi-channel retail software = results,” e Seller, 16 December 2013] Newcombe offers “four steps to free your data to create genuine results. The first three steps involved linking, mining, and using data. The final step involves reaping the benefits of the first three steps. Concerning linking data, Newcombe writes:

“Every business maintains records of transactions, customer interactions and purchase history. Commonly these data stores exist in isolation, with each business unit retaining responsibility for their own system. Even where an ERP platform underpins business operations, ancillary operations still maintain their own systems. CRM data is managed by Sales and Marketing for instance. Historically data has been kept in silos partly for security, but mainly because systems were designed to serve a single purpose. Sharing data between systems and business units is still a relatively recent innovation. Linking systems is essential to unlock additional value hidden in the data you already own.”

I have written a number of posts in the past detailing the problems that arise when information remains siloed. I agree with Newcombe that data integration is the first step to making data as useful as possible. What Newcombe doesn’t note is how difficult data integration can be to achieve. Each siloed dataset is likely to use a different format and different terms. Integration is likely to involve some kind of natural language processing to ensure the right kinds of data are connected so that important relationships can be analyzed. That is a non-trivial challenge. Concerning the mining of data, Newcombe writes:

“Multi-channel software solutions can provide a platform that links disparate systems to create a holistic view of your company and customers. This data can then be used to:

• Segment your customer base to create target groups.
• Identify product buying trends.
• Correct inaccurate records and disseminate updates between systems.”

In the world of targeted marketing, customer segmentation goes much deeper than age, gender, and/or location. However, not all analysts are true believers when it comes to targeted marketing. For example, Michael Hickins writes, “We’ve all heard the pitch for over a decade: technology will help retailers send contextually relevant marketing messages to mobile devices of consumers wandering around malls and shopping districts. But despite advances in telecommunications infrastructure and data collection and analysis, there’s little proof that any of this actually sells so much as an extra pair of jeans.” [“In Retail, Culture Trumps Technology,” Wall Street Journal, 16 January 2014] Before dismissing targeted marketing out of hand, however, Hickins notes, “The problem … may not be with the technology. Ram Menon, president of social computing at Tibco Software Inc., says ‘culture plays a big role in how successful this is.'” Hickins goes on to explain that Asian consumers are much more likely to respond to a targeted message than American consumers. Those are exactly the kinds of insights that good data mining can reveal. Concerning the use of data, Newcombe writes:

“The data mined through the multi-channel system can then be put to use, improving business efficiency or increasing revenue. Suggested uses for ‘mined data’ include:

• Targeted mailshots or email campaigns based on new target groups.
• New product creation based on observed trends or ‘gaps’.
• Clean up data sets to ensure records are accurate and legally compliant.
• Improve internal operations where weaknesses or failings have come to light.

In terms of multi-channel integration, the data should be used to improve marketing efforts. Predicting response rates and offer success becomes much easier when equipped with historical evidence. Marketing automation also becomes much simpler, as your team can accurately identify what does and does not work, tailoring campaigns months in advance with a high degree of accuracy. [According to BtoB Magazine,] ‘37% of marketers say their biggest roadblock to effective use of segment targeting is lack of data on users.’ It is also important to realise that customers expect personalised communications and marketing. Your business has a responsibility to know them and communicate according to their preferences. [According to MyBuys/the e-tailing group,] ‘50% of consumers expect to find personalised merchandising on the home page, [and the] merchant’s recommendations’ role on the product page grows in importance as over 60% expect merchants to recommend similar products in addition to related items.'”

In other words, consumers prefer seeing relevant offers when they are shopping. Jessica Galbraith asserts, “Knowing what your customers want, and how they act and react, is at the cornerstone of any truly successful business model.” [“Understanding Your Customers through Big Data,” RIC Centre, 3 January 2014] She concludes, “Big Data may hold unlimited opportunities for the future of marketing, but companies must be open to exploring new concepts and data integration tools as they come along. Understanding a customer has never been simple, but through technology and new forms of data, we have unlimited resources to tap for the future.” If you heed that advice, you may, in fact, be able to reap the benefits of your efforts. On that subject, Newcombe writes:

“Multi-channel integration is an investment that keeps generating returns. Not only do finely targeted marketing campaigns yield higher returns, but each campaign also generates new data for further analysis. Multi-channel software also extends beyond linking existing systems. Data can be collected from ecommerce sites, PoS terminals in store and any other point at which customers interact with your brand. With each iteration of your automated marketing cycle, new, valuable information is obtained, ready for further analysis.”

The game between marketers and consumers has been played since the first the trades were made in ancient city settings. Never before, however, have marketers been able to gather and analyze as much information about consumers as they can today. Even skeptics have to admit that having better information can change the game. Targeted marketing sounds easy; but, doing it well involves the right technology, the right data, and the right marketing strategies.