(An excerpt from my college thesis... fyi time is relative. Pretty neat.)
The new marketing mix: Message, Media, Math
Marketing in the classroom does not translate well to the real world because it is fundamentally not a predicative science, despite how much it wants to be. Physics is a predictive science because force equals mass x acceleration always. Biology is a predicative science because plants take in our carbon dioxide and exhale oxygen always. Marketing is dependent upon people doing things -- but people are random and irrational beings -- and as such you cannot predict how humans will act, even though economics insists otherwise. The result is that the old school marketing mix (aka the "4Ps") is not totally relevant in the digital economy.
My prescriptive and more realistic model is 1) Message 2) Media and 3) Math. The message is what you say, the media is where you say it, and the math is how you measure it. I talked about the Message and the Media in a recent post on content marketing technologies, so now I want to talk about the Math. Math is a general term used for the quantitative methods to measure and optimize marketing. Marketing unmeasured is useless, because without performance marketing is an unjustifiable expenditure. The quantitative methods you use for such measurement could be very complicated or quite simple -- the point is you must measure your work or risk being fired.
Data != Insights
Generally speaking I advise that all companies are reliant upon the growth of 3-5 key performance indicators at most. Pump those numbers up and your business will grow, everything else is supplementary. This puts an interesting perspective on your business intelligence strategy -- you have to figure out how to measure the right things only, because more data is not necessarily better data. In fact, data is not useful just because it is "data". The goal of business intelligence is to find insight, because insight tells you things you can do to make your business better. If you cannot derive insight from your data you are doing it wrong.
New Technologies
Early web analytics software evolved to serve the needs or early web businesses. Technology was quite limited back then, and so the kinds of things you could do and measure on a website were also quite limited. Everything has changed because now we have we have social, mobile, and SAAS (and whatever is next). The amount of data you can measure, and it's different types, has grown exponentially. I have listed below some companies that do business intelligence for technology companies trying to make sense of this new and bigger data. This is definitely not and exhaustive list, so do your own research before you buy.
CUSTOMER ANALYTICS
https://www.kissmetrics.com/
https://mixpanel.com/
https://www.woopra.com/
https://keen.io/
OPTIMIZATION
https://www.optimizely.com/
http://unbounce.com/
https://vwo.com/
http://www.crazyegg.com/
https://qualaroo.com/
CUSTOMER MESSAGING
https://www.intercom.io/
http://customer.io/
SOCIAL ANALYTICS
http://datasift.com/
http://gnip.com/
http://www.crimsonhexagon.com/
http://simplymeasured.com/
https://www.ubervu.com/
http://www.sysomos.com/
http://topsy.com/
MOBILE ANALYTICS
http://www.flurry.com/
http://www.localytics.com/
https://apsalar.com/
MOBILE DATA
http://appfigures.com/
http://www.appdata.com/
http://www.appannie.com/
CUSTOMER SUCCESS
http://trak.io/
http://www.gainsight.com/
http://www.totango.com/
REAL TIME ANALYTICS
https://chartbeat.com/
http://clicky.com/
https://www.gosquared.com/
DATA WAREHOUSING
http://rjmetrics.com/
https://www.custora.com/
DASHBOARDS
https://www.geckoboard.com/
https://sumall.com/
http://raventools.com/
SEO
http://moz.com/
http://www.semrush.com/
http://www.searchmetrics.com/
THERMONUCLEAR
https://segment.io/
Resist Complexity
There used to be a small oligopoly of business intelligence companies, but the proliferation of new channels and platforms has spawned a new market of BI technologies to serve it. Indeed you can collect more data and measure it in more ways now, but that is not the point. Remember, data != insights, so more data != more insights. An overbuilt data system is your enemy. Your goal should be to determine the few KPIs that are most important to your business and then to implement the tools that will help you measure and optimize them best.
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What tools do you use? Tweet me @yes to let me know.
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