The Future of CRM – Genuine Intelligence from an Artificial Source

10 Dec 2018

If you jump onto any tech blog or happen to come across some marketing material from IT giants, Artificial Intelligence (AI) is the hot topic shaping the marketplace. But the term does seem to get overused and maybe undervalued at times AI is used to describe any type of automation, something which many often get away with due to a lack of detailed general knowledge.

So, what actually is AI? Well the dictionary definition puts it as – ‘any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.’ 

Pretty broad right? To help clarify what these means in my industry, I’d like to look at some of the key AI advances I expect to see in the CRM market over the next 12 months which may shape the way tasks are performed intelligently on the behalf of you, our user.

Lead Forensics

Most CRM systems are based, at their heart, around improving the efficiency of the sales process for a business. For generating new business, this typically starts at the Lead/Prospect stage and for many Sales Directors, the key way to boost efficiency is to prioritise the needs of the highest value prospects.

This is done through something known as lead scoring.

Lead scoring isn’t something that’s new to the market, but it is something which I believe is often wrongly classed as ‘AI’ for purely marketing reasons. Currently, most CRMs score leads on fairly straight forward conditions, i.e if the prospective company size is 30+ or the expected spend is higher than average, give them a high score.

The CRM hasn’t really applied intelligence, it has just followed the rules set out by the administrator.

True intelligence would sit outside these rules, with the CRM using trends of the past to inform decisions of the future. Soon, we may see systems recommending next steps based on previous results of leads with a similar profile.

An example being leads from a certain industry over the last 6 months are taking longer to close on a deal. So instead of just giving them a medium score, your CRM extends the expected close date and adds a warning to that effect. It may even automatically schedule the a few extra calls in advance to maximise the chances of success.

When it comes to prospects, Artificial Intelligence won’t just enable us to build up a score but instead, map out the ideal process which is tailored to their needs to get them over the line intelligently.

Pipeline Forecasting

Almost an extension to the above, pipeline forecasting is used to give a manager information about how many sales are likely to come through in the future and what the revenue of those might be. This allows them to make plans related to hiring and other outgoings.

Soon enough I think we’ll see systems taking historic sales data, mapping it against data of the present, to give us intelligent insight into the future. Giving a secondary forecasting that maybe goes even further into the future.

Let’s simulate a second situation – from historic data, your CRM knows that Construction companies of employee size 10-20 close 50% at an average order value of £3,000. The CRM can then look at the current pool of prospects and, for those that meet the criteria, apply a baseline average expected revenue to give me a forecast of my prospects.

It would then update that on a rolling, daily basis using the newest data available, something a set of simple rules couldn’t do.

Contextual Recommendations

As the name suggest, we need our CRM systems to help us better understand, manage and maximise the relationships with our customers. Whilst it’s undoubtedly true that they already play a major part in making this happen, with the data at hand and powerful computing, we need our systems to calculate the trends and highlight the issues we just can’t!

We’ll begin to see our CRM systems give us recommendations on next actions based upon the existing relationship with our customers.

Here’s a great example – a normally very satisfied customer suddenly starts raising a larger than average number of tickets with your support team in a short period of time. Your CRM system knows that, for this customer, that’s not normal and automatically schedules a call activity for their Account Manager to check in.

On the flipside, a customer who is regularly engaging with support (and raising lots of tickets) to expand their functionality goes quiet for a few weeks – again, the CRM system let’s their Account Manager know something might be amiss by scheduling an activity or raising a warning!

The intelligent thing here is the context. An automated system rule just wouldn’t cut it as every customer, their needs and their behaviours are entirely different. Soon CRM systems will be able to track hundreds of individual ‘norms’ and let you know when it’s time to step in!  

Optimising Delivery

Whilst the art of sales calling is by no means dead, in the last decade we have seen the power and effectiveness of email marketing rise and rise. With the internet now a completely ingrained part of society, getting your email marketing strategy right is essential to staying alive in the business world!

As we’ve seen in previous examples, AI can empower us to make truly intelligent decisions when it comes to our marketing content. Taking detail data from previous campaigns, soon we’ll see CRM system advising and optimise email marketing campaigns on our behalf to boost returns.

This could be a simple as suggesting the best times to send or going further and suggesting the best templates structures, layouts and designs to appeal to different markets. We may even see varieties of the same templates being sent to individuals based on their demographic – again in a bid to boost effectiveness!

Enhanced Data Management

Every example I have listed above all rely on the same underlying foundation – great data. For AI to truly bring us amazing benefits, the way that we gather, store, analyse and manage data will need to improve.

As the software world becomes more and more interconnected, expect this to happen by default. The rise of IOT devices means more and more data is available on our buying habits (the jury’s still out whether that’s a good or bad thing) and this information will likely be available to increase our data sets.

This gathering of customer intelligence will not only gift us a means to an end, but also save us a laborious job. No more hunting around LinkedIn to get an idea of a prospects interests or jumping onto Companies House to identify a buying organisations spend power – we’ll see interconnected systems getting that data automatically, giving you, the user, the power to act faster and with far more accuracy!

Whether we like it or not, Artificial Intelligence is on the horizon and won’t be disappearing any time soon!

For software organisations, it opens a whole new realm of possibilities and will allow customer the opportunity to transform the way they run their businesses and keep their customers happy!