Applying Predictive Analytics to Marketing Challenges


Quant5 planning ness-050613_final from Doug Levin

Every year, a group of very smart and accomplished strategists and planners gather for an un-conference for thinkers/doers aptly named Planning-ness#. The tagline is "get excited and make things." I like the fact that the group also sponsors a grant each year:

A minimum of one grant of $10,000 will be awarded each year to an individual or small group for the express purpose of undertaking research or other project that stretches the thinking of or benefits creative thinkers everywhere.

Those who are awarded the grant will be required to make their study available to the planning community and share their findings at a future Planning-ness event.

This year, the event is in Portland on September 11, which is the same day I am running the Financial Services Industry Lab at Content Marketing World. It looks like I will need to do better planning next year (pun intended).

In a post I wrote a million years ago at this site, I tackled the topic of revealing yourself to others:

Revealing yourself to others is an important part of the process we call "building relationships," from which we build credibility, trust, and loyalty.

It takes place over time and there are no shortcuts, and yes, your work speaks louder than many words you may say about yourself. Way down in the post, in response to a meme popular at the time, I listed jobs I would like to have:

  1. Strategist – "think and do" tank
  2. Curator – ideas and trends
  3. Chief maker and storyteller
  4. Idea catalyst

Planning-ness is focused on creating the conditions to build meaningful exchanges in support of all my four pillars.

Which is why the example above from last year is so compelling. It delves into how to apply predictive analytics to marketing challenges, still a very timely topic.

Businesses spend hours collecting and trying to make sense of data

We continue to grapple with making decisions without having the necessary information, the proper business context insights, little to no visibility into data from other business units, and often lack the data scientists to make sense of what we do have.

Visualizing the challenges we are now grappling with technology integration, channel attribution, and people skills (I used the slides at the CGT sales and marketing summit, why you see a footer).

Large Gaps in Digital.png Marketing Technology Integration Difficulties
According to SAP Analytics (02/08/13), the top 5 sources of data tagged for predictive analytics are:

  • 54% Sales
  • 67% Marketing
  • 69% Customer
  • 55% Product
  • 51% Financial

In addition, 40% of companies surveyed indicated that “Social (Facebook,Twitter & LinkedIn) had potential value in predictive analytics.

We use a similar process to inform our programs to the one Doug Levin from Quant5# used to illustrate via sample case study (slides 17-30). By and large, this is still about overcoming the challenges listed above — siloes, IT integration, finding the right data sets, thinking smartly about the questions/query set, etc.

What have you seen working well, and where do things fall apart?

+++

Valeria is an experienced listener. She designs service and product experiences to help businesses rediscover the value of promises and its effect on relationships and culture. She is also frequent speaker at conferences and companies on a variety of topics. Book her to speak here.


Leave a Reply

Your email address will not be published. Required fields are marked *