Conversion Rate Optimisation

Does ‘Bribery’ Work In Conversion Optimisation?

I received a question from a colleague and friend who is an SEO (I’ve left his name out in case he may not want to be mentioned for privacy) by e-mail a couple weeks ago that asked:

Hi James,

Do you think the bribe model works [in conversion optimisation]?

My Answer

Short answer

The short answer is: yes, the ‘bribe’ model can definitely work and I would never dismiss it or overlook it.

Numbers based answer

In situations where I’ve tested bribery versus other stuff, I’ve usually found that ‘bribery’ has often helped (as long as the offer has been right) but sometimes the improvement is a lot lower than other things. (Elaboration below).

The longer answer

Yep, the ‘bribe’ model can definitely work (or as Robert Cialdini in his book Influence calls it ‘Reciprocity’) and is a powerful tactic for influence and persuasion (Getting people to say ‘yes’ which is really what all conversion optimisation is about at the end of the day.).

I’ve heard of people virtually using Robert Cialdini’s book as a conversion optimisation methodology in itself. In my experience, there’s a lot of wins to be had in his principles, which are:

  1. Reciprocity (can also be thought of as ‘bribery’);
  2. Commitment (and Consistency);
  3. Social Proof;
  4. Likability;
  5. Authority;
  6. Scarcity;

It should be required reading for anyone looking to get into sales or marketing in my opinion.

That said, the “challenge” with “bribery” and “reciprocity”, in my opinion, is this:

  • When it’s done right and it works, it’s not really bribery or reciprocity – it worked because you provided something that your customer considered to be of value, possibly for free or at a discounted rate, and ultimately – you gave the customer what they wanted. 
  • When it’s not done right and it doesn’t work, it’s usually because you were trying to give the customer some junk they don’t want (perhaps it’s what the company thinks is valuable – but actually isn’t valuable from the point of view of the customer.)

Therefore, if you think about it: bribery done well is really just giving the customer what they want. Giving the customer what they want is one of the most powerful tenets underlying how to craft a superb offer. In my experience, a lot of companies and marketers fail to really understand what the customer actually wants. Think about how many websites are out there offering e-books for free.

Now, think of how many people you know who actively love ebooks or pay money for ebooks or really like them? Not so many. (Kindle and eBook readers are a bit different. If the offer was “A free book on your Kindle” that might be more valuable. But think, who actually considers eBook PDF downloads valuable? Very few indeed.)

Consider this: you might use all reciprocity in the world, demonstrate social proof like crazy, be likable, be authoritative and be scarce – but at the end of the day, if the customer doesn’t have a need for what you’re selling, doesn’t consider it valuable or doesn’t understand the value – they won’t buy. The first and most important job for any marketer is to explain to your prospect why they should buy from you rather than someone else.

A/B Testing

Is It Better To A/B Test For 95% Statistical Significance Or 99.95% Statistical Significance?

An excellent question was raised by one of my A/B testing clients at Web Marketing ROI. Adam asked:

“Just curious to know when you prefer to use 95%+ versus 99.95%?”

My Answer:

It’s an excellent question and one that very few A/B testers think about or understand.

When we say “95% statistical significance” – we’re (in simplistic terms) basically saying there is a 5% chance that the results could be a statistical false positive.

When we say “99.95% statistical significance” – we’re (in simplistic terms) basically saying there is a 0.05% chance that the results could be a statistical false positive.

Therefore, 99.95% is much more certain than 95% and obviously preferable.

It’s not as simple as that though.

There is also a question of the additional time it may take to achieve 99.95% statistical significance versus 95% statistical significance.

The additional time required to reduce the likelihood of statistical anomalies by 4.95% has an associated opportunity cost.

In other words: is it worth investing an additional X days (where X can be a large number) in increasing the certainty of this test or would be better off ‘playing the odds’ (with the odds in our favor) and using valuable testing time invested in finding another statistical significant conversion improvement? To be able answer this intelligently, we need to calculate what X is.

Assuming your current numbers extrapolate out over the next 7 days, it might look as follows:

Calculating Statistical Significance (MS Excel)

As you can see from the above: 95%+ statistical significance might be achieved on Day 4, but 99.95% statistical significance is still not achieved at Day 10. Your traffic numbers and number of daily conversions are more than 5 per day so getting to 99.95% is a lot easier for you than some companies with less daily conversions.

Another way of thinking about it is imagine you were in a casino where the odds were permanently rigged in your favor at 95% – the logical way to generate an infinite amount of money would be to keep making as many bets as possible and eventually ‘the house (i.e: you) would win’. Although you could possibly tweak the system to be 99.95% accurate, you wouldn’t need to because given a long enough period of time and enough bets (of small amounts relative to your total resources), you’d be a winner.

At 95% statistical significance, 1 in 20 A/B tests might be a false positive. But you’ve still got 19 accurate real winners in less time.

At 99.95% statistical significance, 1 in 2000 A/B tests would be a false positive but if you were going for 99.95% statistical significance – you might have only had the chance to execute half as many tests.

Given the choice between 20 tests at 95% statistical significance vs 3 — 10 tests at 99.95% statistical significance:

The former is better in terms of real conversion improvement, statistically speaking (‘playing the odds’).

Assuming you had an infinite amount of time and no opportunity cost (which isn’t really realistic in business), 99.95% would be better.