New to statistics and I'm sure that will be obvious!

I'm taking over from someone at work they conduct some analysis on something :

A test group are receiving an email.

A control group are not.

The two categories are:

Does sign up to online account management

Does not sign up to online account management

Here are the observed results :

Test: 12870 signed up, 49184 did not.

Control : 1535 signed up, 9993 did not.

If i do a chi squared test I get the following results

Chi squared stat: 340.38

P value < 0.00001

This shows the result to be highly significant, aka we reject the null hypothesis that there is no association between group and the categories.

However, my colleague has then chosen to calculate the phi coefficient which comes out at 0.068145

The above was calculated using R. I assume you don't need to multiply is by 100 or anything?

From Google I can see that a figure of 0.068 means that there is 'no or negligible relationship'.

My question is:

These two results completely contradict each other. Chi squared is incredibly significant and phi says there's no association. Is there an association here or not?! Does receiving the email make you more likely to sign up?

Are there some rules as to when to use the phi coefficient or just stick to chi squared or vise versa?

Could there be rules regarding sample size? I thought my numbers above are fairly large? We're not talking single digit.

I'm aware there is other methods of working out correlation so any advice or links to particular articles that would help would be appreciated.

Thank you

Dr Strangelove