This is a guest post from Feather Hickox.
The average consumer receives over 16,000 marketing messages each day. Marketers face a daunting challenge to break through that volume of noise.
This challenge has given rise to Big Marketing – the use of Big Data analytics to develop personalized marketing messages and offers on a massive scale.
Based on my team’s work with many of the largest retailers in the world, we’ve compiled a list of seven essentials for turning Big Data into effective, profitable and highly targeted Big Marketing campaigns.
1. Develop a “back to the future” understanding of individual customers
Remember when the corner butcher knew who favored pork chops and who liked filets? This type of old school knowledge of customer needs, attitudes and propensities is new again.
Today analytics is being applied to Big Data in ways that make is feasible for businesses to get to know millions of customers on an individual basis. Only now this knowledge is gleaned by identifying behavior patterns found in the vast quantities of bits and bytes from point-of-sale devices, mobile devices and online activity.
While respecting consumer privacy, companies are able to develop this more complete picture not only from what customers say (in online comments, ratings and profiles, blog posts, tweets, etc.) but also from what they do (data from in-store and online purchases, mobile payments, web searches and browsing etc.)
2. Find the real predictors of customer purchasing behavior and other propensities
What motivates customers to take action is often a complex, subtle interplay of factors.
As companies shift away from traditional methods of sending out offers based on operations-driven programs towards generating individualized offers based on customer propensities and behavior, it’s important to avoid using simplistic behavioral triggers based solely on basic business rules and personal judgment.
Is it effective, for instance, for a bank to create a business rule that says “whenever customers with acceptable risk scores spend more than $400 on tires, send them an offer for an auto loan?” Probably not.
The behavior patterns that accurately predict whether a consumer is likely to purchase an automobile in the near future are more complex than that.
3. Scientifically balance all the factors in complex marketing decisions
With easy-to-use simulation tools, marketers can modify one or more constraints in a marketing scenario to see how the optimal decision strategy shifts, exploring trade-offs and choosing the best operating point for their business goals.
The most sophisticated Big Marketing projects generally encompass dozens, sometimes even thousands of models employed simultaneously.
4. Answer “million dollar” marketing questions
Using Big Marketing techniques, companies can find answers to questions they believe will give them an edge. For example, “Will 10% off be more effective than free shipping or than simply telling customers that the desired item is in stock and will be reserved for a short period of time?” and “Is offering 12 months of interest-free credit necessary, or will 6 months be just as enticing?”
Big Marketing analytic techniques can help retailers align operations-level customer decisions with executive-level direction. In light of a company’s revenue goals, sales objectives and profitability targets, and the customer’s current and future value to the company, what is the most profitable offer?
5. Engage customers in individualized multi-channel relationships
A customer who is planning a bathroom remodel is a prime target for individualized offers. The first customer touch point might be an email with renovation tips, the next might be a call or email with an offer for a credit card upgrade, or possibly home improvement financing.
The next communication might be a text message offering an appliance coupon with a qualified purchase. Another email might offer design tips and entice the customer to consider an in-store consultation.
Depending on the customer engagement at every step along the way, the offers can be tweaked and targeted to the customer’s individual needs and propensities.
6. Learn from what is happening in the market right now
Big Marketing decisioning is responsive to constant change. At the back end, predictive data elements are constantly refreshed according to daily customer-level data. At the front end, companies use analytic learning loops to rapidly measure how customers are responding and to adjust decision strategies where necessary while campaigns are still underway.
7. Launch forward-looking experiments to get ahead of competitors
Using analytic learning loops in conjunction with systematic experimental design, companies may discover opportunities that are not evident to competitors and gain forward-looking insights into how customer behavior is evolving.
In addition to testing variations on well-performing decision strategies, companies should test strategies that are beyond the edges of business as usual and organizational comfort zones. As stated by Ovum, “Big Data is a change of mindset regarding the art of the possible.”
Of course, these don’t just apply to marketing but can be applied across various other channels too. But as a very basic to what companies should be doing in the marketing space next year, they should definitely be a starting point.
How about you – what have you planned for 2013 to keep you ahead in the marketing game?
About the author: Feather Hickox is Senior Director, Industry Marketing for FICO. She works with retail and CPG clients who capture, analyze and act on data from millions of transactions each day. Feather is a contributor to the FICO Labs Blog.