Ask almost anyone in almost any organisation what they think of meetings and they’ll pretty much all say the same thing – “We hate meetings”.
Whilst there is a lot of feeling that meetings are bad, there is often very little or no solid data to back it up in the organisation.
Mayalytics is our brand new service to help any organisation measure and visualise their meeting culture and provides high quality quantitative and qualitative metrics to drive improvements.
Built to Visualise Meeting Culture
As we built Amazemeet we found we had lots of users but not many customers.
We also found that one of the key reasons for this was that decision makers in our users’ organisations needed data to see if they had a problem with meetings in their company.
Mayalytics was born with the belief that we could help leaders and decision makers improve their organisation by giving them useful metrics about their meeting culture.
8 Key Metrics Right out of the Box – for free
Using the data we get from your meeting invitation and feedback from specially devised micro surveys, we add a dash of Artificial Intelligence to make sense of the data and provide 8 key metrics about an organisation’s meeting culture:
Meetings per Month: the number of meetings per month across your organisation
Total Meeting Time per month (in hours): how much time meetings are taking.
Employees Meeting Time per month (in hours): how much employees’ time is spent in meetings.
Employees Meeting Wasted Time per month (in hours): how much employees’ time is wasted in meetings.
Meeting Costs per month (in US Dollars): how much meetings are costing the organisation per month
Meeting Wasted Cost per Month (in US Dollars): how much of the cost of meetings is wasted.
Employee Sentiment before meetings (in %)
Employee Sentiment after meetings (in %)
Incredibly Easy to Use
One of the best things about Mayalytics is how easy it is to use.
To get your Meeting Culture data flowing, all you do is what you’ve always done for meetings that you organise- simply invite an additional email address and we take care of everything else.
Getting started is super simple and quick.
Our “Getting Started” video explains everything you need to know to get it started.
Start using it right now and building up the data you need to get these useful metrics.
Pricing can be complicated in any startup. Amazemeet is no exception, though we think a few things we have learned in trying to devise plans and prices recently have helped us get a better attitude to one of the most important aspects of launching a SaaS business.
Pricing can also be exceptionally simple – you can make numbers up out of thin air with little or no thought for whether anyone will pay that price for your product (what I call ‘the blue pill’).
We chose to do a bit more (what I call ‘the red pill’). More research and more educated guesses to get data we could make decisions on. More importantly, we wanted a process to emerge out of setting and reviewing our pricing so that we could use it over and over again.
We’d like to share where we are and what we learnt trying to price our service.
Where we are now
We recently finalised our last round of pricing experiments and created a new pricing model combining the best bits of the various experiments and what best supports our current phase of our strategy (i.e conversion).
So how did we get here?
I’ve tried to distil the chaos of the last few weeks into 5 key learnings. If you are interested in the stuff that isn’t written – the emotional rollercoaster, the techie bits of experimentation etc, then please ping me here via comment or on twitter (@amazemeet) and I’ll be happy to share that.
1. De-stress pricing through iteration and experimentation
Pricing can be stressful. We found the biggest source of stress was to believe that whatever model we came up with had to work for everyone, forever!
If there is one enduring strength in our team it is that we are almost entirely pragmatic and agile in our thinking and in our execution. This has helped us develop a healthy attitude to risk. We use iteration and experimentation all the time for everything.
To take the stress out of pricing, we’ve accepted that:
We can change it anytime if it isn’t working
We will review it regularly to see if it needs to change
It doesn’t have to be good forever, just until the next change.
The core of iterative experimentation is accepting that you don’t know something, you are doing reasonable things to learn more and that you can change at the next turn. [su_tweet tweet=”Accept that you don’t know, you’re doing things to learn more and you can change at the next turn” url=”http://bit.ly/1TL2tro” via=”amazemeet”]Tweet this[/su_tweet]
2. Understand who you are pricing for and design for them
This sounds like a no-brainer – especially if you have been more or less tracking certain segments or user and customer types. Just as different users want different features, different customers have price levels they will pay – often regardless of how valuable your product or service is. [su_tweet tweet=”Different customers have price levels they will pay – often regardless of how valuable your product or service is” url=”http://bit.ly/1TL2tro”]Tweet this[/su_tweet]
Amazemeet is a B2B service, we enable businesses of all sizes to have better meetings. This range presents complexity when we try and price to suit all businesses and keep us sustainable. The complexity comes primarily from the different price levels that specific types will support (large corporations might support higher levels, whilst small, modest companies support more modest pricing).
Complexity also comes from how those segments purchase stuff – large corporations often have restrictive purchasing policies that prevent the person with the problem from easily purchasing their chosen solution. Smaller, more independent business often don’t have that constraint.
Our pricing model had to support the price levels that would have credibility with the segments and navigate the purchasing restrictions purchasers in each segment to help them buy.
So for smaller sized companies and independents (like freelancers) we introduced a monthly plan and for the larger corporations where the effort of approving a $5 purchase is about the same as seeking approval for a $500 purchase – we introduced yearly plans to help them get the most out of that approval step.
3. Understand Your Goals for Pricing and Design to Achieve Them
We started out thinking pricing was simply about setting a price for your product and generating revenue – we were pretty mistaken. Sure it is about revenue – and so much more.
So we thought a bit more deeply about our goals – or what we wanted our pricing model to help us achieve and came up with:
help us to grow our user base (so pricing is not a barrier to usage)
help users become customers (so there is clear value to being a subscriber).
To achieve the first goal, we experimented with a freemium model – offering a free tier to let people try out the service (we believe we are the only ones with a meeting design model like Amazemeet on the market – it takes some getting used to!). This worked well – a little too well perhaps.
It would be silly to think it was just because we had a free plan that people joined. We are also lucky to have a naturally viral product.
We are seeing a stable growth in users and in organisers, but we were not seeing any growth in customers. When we spoke to users about the value they were getting from using the platform, they told us of improvements in clarity and follow ups. We’ve known that users found the platform useful (this has been fairly consistent feedback since the beta in June 2015) – what we struggled to determine was if it was also valuable!
Despite the success of the freemium model in helping us grow the user base, it created a secondary problem for us – which we encouraged by not differentiating plan features early enough. So we replaced it with a 7-day fully featured trial experiment and put all our existing non-subscribed users on the trial.
Whilst this has had little or no effect on the rate of sign ups, it does help to funnel serious users of our platform to a subscription plan. But it is early days yet – the first set are expiring this week and we are eagerly awaiting the result of that experiment.
Remember this: Users *hate* anything being taken away from them. Especially if it was once free. [su_tweet tweet=”Users *hate* anything being taken away from them. Especially if it was once free.” url=”http://bit.ly/1TL2tro” via=”amazemeet”]Tweet this[/su_tweet]
Incidentally we still have a free tier – it is just not publicly advertised. It offers unlimited meeting attendance but no meeting organising. It is the plan people revert to when they take no paid subscription.
4. Be willing to lose users – but understand why
There are few things more flattering than people signing up to use something you built.
But there are the right type of users and the wrong type of users. The right type of users use your service regularly – or as regularly as you intended. The wrong type use it much less than you intended and generally don’t come back and rarely tell you why.
As we experiment with Amazemeet – we recognise that the more specialised we become in how we design for the segments we are focusing on – including our pricing – we will inevitably lose some users. This is why it is super-important to not do too many things at once – because you want to know why you might lose those users.
For example, when we experimented with hard limits on the now-deprecated free plan, we saw some usage drop off. We recognised that there would be some users who wouldn’t upgrade to a paid plan once their 5 meeting limit was reached. We could even tell who might react like this by their usage patterns – they were not regular users of the platform and this restriction just persuaded them to stop.
This may be counter-intuitive, but I would rather have 1000 committed users than 10 million ghosts – and if I do anything to make the numbers that I base my decisions on that much clearer aligned with reality – I might just make better decisions.
Users are not all equally valuable. Knowing what makes a user valuable to your business helps you value and invest in that relationship better. Be prepared to cut back investment on those user relationships that are not helping you to your goal. [su_tweet tweet=”Be prepared to cut back investment on those user relationships that are not helping you to your goal.” url=”http://bit.ly/1spIjwl” via=”amazemeet”]Tweet this[/su_tweet]
5. Regularly review the drivers of your plans and pricing and adapt them
We aren’t done yet and we aren’t there yet. ‘There’ being stable and growing revenue, but we have had the most positive feedback so far on usefulness and on value.
The goals of our pricing can change, the behaviours we want to encourage can also change. We will be moving to other segments – either geographically or otherwise. We might pivot our features or the vision. Each one of these changes will bring new drivers to our pricing model and cause us to review.
In anticipation of this – we ask ourselves every month – “Is this pricing model still the most effective one for our goals and constraints’. If the answer is ‘Yes’, we move on. If not, we go deeper and explore what the next iteration and experiments ought to be.
There you have it – this is how we are doing pricing in Amazemeet. At least for now. What would be a great help right now would be your honest opinion and probing questions about this.
Is there something that just doesn’t make sense about this? – I’d love to hear it.