Six Principles of Psychology which Affect Analytics and Decision making

Wednesday, 30 October 2013 0 comments

Six Principles of Psychology which Affect Analytics and Decision making



The success of analytics within a business is not just about numbers, technology and processes, it's about how we integrate between analysts and marketers.

This was the thrust of a fascinating presentation by Suniel Curtis, Head of Web Analytics and Insight at Hays, formerly of lastminute.com.

1. Create a story, don't just use numbers
While numbers can be very convincing, this isn't always enough to convince stakeholders to take action.

Instead, you need to be able to use the numbers to tell a story and bring the data to life.

2. Provide just enough data
Often, meetings don't produce enough decisions to take action, but instead can often end with requests for more data.

People will delay decisions if more data can be found, even if it's irrelevant.

Suniel referenced Princeton research paper, On Pursuit and Misuse of Useless Information. Here's a very apposite quote from the paper:

Decision makers often pursue non instrumental information--information that appears relevant but, if simply available, would have no impact on choice. Once they pursue such information, people then use it to make their decision.

Consequently, the pursuit of information that would have had no impact on choice leads people to make choices they would not otherwise have made.

The lesson here? Present the minimum amount of data required to make a decision.

To illustrate this point, he used an example from Hays. The company advises job applicants to update and maintain their social profiles to improve their employability.

However, many tend to ignore this advice but one key stat changed this: 90% of hiring professionals view social profiles.

That's all the data that was required.

3. Use the voice of the customer
Data can do a lot, but using customer feedback can be more powerful in convincing stakeholders to take action.

Suniel used an example from a previous role at Hilton, covered here in Marketing Week. He had identified an issue where customers were encountering unintended error messages during the booking process, causing them to abandon their purchases.

Suniel calculated that this error could cost up to $3bn per year in lost bookings.

However, identifying the issue wasn't the end of it. People higher in the business needed to be convinced, with some dismissing the problem, saying that customers would just call instead.

By looking through customer feedback and providing examples of angry customers who had abandoned their bookings, these stakeholders were persuaded to act.

4. Don't push a choice, push a test
Suniel used the example of the 'ugly baby problem'. In other words, if analysts go to marketers or developers with problems, they are insulting their 'babies'.

A developer or marketer may have ploughed months of time and effort into a campaign or website, and doesn't want to hear that this effort wasn't worth it.

The recommendation to give choices, not absolute recommendations. This can make it easier for people to accept the data, as they are brought into the process.

5. Co-locate with stakeholders
Rather than having analysts grouped together on same bank of desk, apart from everyone else, integrate them with the parts of business they are servicing.

Then, the analysts are in with the decision makers and joining their meetings. This enables people to form ideas together, based on the data.

Business should be cautious here, as analysts do often like to work together.

Therefore a balance needs to be struck, perhaps they could spend one or two days a week working together, or congregate for regular meetings.

6. Change tack when you hit resistance
Here, Suniel quoted Hans Rosling, a Swedish doctor, academic and speaker:
When I have an argument with someone, even with someone I am not very close with, I can't sleep at night thinking about it. It's terrible.

But I still manage speak out frankly because I have also been gifted with the ability to read people. I can sense when they start to get irritated with me, and then, I shift.

The point here is that analysts need to understand that they can create strong emotions among stakeholders when they present reports and recommendations.

Sometimes a change of approach is needed. As in the Hilton example mentioned earlier, if stats alone aren't working, bring in things like customer feedback.


The conclusion? Success with analytics is not all about numbers, technology, data and processes. It's about how we integrate between analysts and marketers.
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