There are a lot of ways to do dumb things in sales and marketing processes. Perhaps there are a lot of ways to do it right as well – maybe.
Not to sound too trite but the best way to automate sales and marketing is the smart way. The smart way should involve advanced analytics utilizing machine learning procedures which include predictive recommendations and prescriptive actions. If that is a mouthful, think artificial intelligence (AI) applied to sales and marketing.
AI is not as scary as it sounds to most businesspeople. Sure, there are very, very advanced things being done in the area but the term also includes analysis of patterns in business transaction and CRM data to spot patterns, trends and groupings.
Of course, the headlines and most press notoriety goes to the cutting-edge of AI. However, no longer are AI projects only for large companies or done by costly consulting firms. Midsized businesses can now do their own AI analysis. The technology and processing capacity improvements of the past several years puts AI within reach of “regular” companies. For sales and marketing automation, simple predictions this could include analysis like best time of the day to call an individual customer contact, most likely first product ordered by a particular type of prospect, predicted response rates to an email, and so on.
One potential high impact use is to examine jointly CRM and website activity. More often than not, every customer and prospect has a unique history of communications and website use. Teasing actionable information from a report is impossible since a person looking at the data, even in a great looking dashboard, cannot find meaning and correlation between the seemingly unrelated histories.
Bringing CRM and website data (and social media if applicable) together is not difficult. Finding the similarities between the multiple data sets does require some thinking. The harder part is finding meaning and patterns once the data is merged.
More than likely, there are patterns. Broad scale patterns might exist based on customer or prospect type. Or, prospects and customer might show similarity based on size or level of contact in the organization. Other patterns or groupings could potentially exist but are not visible when looking at tables and charts.
More than likely, an analyst is going to look for sure things in the data – if the prospect does action A and B then the sales response must be C. That is how most people work but that level of certainty is going to be impossible to find except in isolated circumstances. There are just too many variables. But don’t give up!
There are still patterns in the data and in the behavior of customers and prospects. The best way to look for them is from the perspective of probability – for example, if a prospect does A and B then there is a 60% chance they will respond to automated process C. It is not a sure thing but there is a pattern. And, it is actionable
AI can find those patterns. More importantly, AI analysis is repeatable so when the world changes the AI predictions will keep up. Rather than have analysts pour over massive amounts of data, the AI algorithms find the patterns and highlight how they are changing.
Those AI processes run against CRM and website data and inform companies on the better ways to automate their sales and marketing processes.