Think of sales and marketing campaigns in a traditional sense and you may well dream up the heady days of billboard advertising or the golden age of television advertising. In short, these days are gone.
In a modern sales and marketing environment, rather than the art of advertising, there is now a science to marketing and as a result, sales. This change in the way sales and marketing teams are operating has also given rise to a more considered, results-driven approach.
Rather than approaching a marketing campaign or sales drive with a vague goal in mind, these days you are more likely to kick off a campaign with figures in mind both in terms of previous proof and predictable results. This trend is by no means new, but the advent of a more resilient and functional level of artificial intelligence (AI) has meant data is now more useful than ever before.
Profiling and evolving data
The hallmarks of a solid marketing campaign now involve data and building up an image of the end-user. The ways in which a typical customer profile is created has however changed from simply positing an A, B and C type.
Sales reps can spend hours trawling through LinkedIn and clicking through company websites. Through creating buyer personas, AI can speed up this process, making lead generation faster and easier. A buyer persona is a semi-fictional representation of your ideal customer, based on real data. AI can take the data, analyse it at speed, and continually update the persona in real-time. This makes sure your buyer personas stay relevant over time.
Steps to predictive sales and marketing success
Now, multiple levels of detail can be drilled down into and more specific, dynamic profiles can be set out. The way data is managed, updated, and in effect, cleansed also means businesses wanting to ensure they are pitching, engaging with, and marketing to the right individuals has more chance of reaching the right people than ever before. Dynamic data systems, which can be updated in real-time and often automated, are making the difference between leads remaining prospects or becoming valued clients.
Improving internal teams
As well as prospecting and nurturing client relationships through AI, B2B sales managers can use the same kind of technology to supervise their own internal team’s performance. A recent study by InsideSales.com found that six out of ten respondents (61%) saw the value of adopting AI to streamline day-to-day processes, of which this is just one.
This kind of streamlining can be done by assessing revenue pipeline, seeing which salespeople are likely to hit certain quotas, getting a snapshot of which deals stand a good chance of being closed – all are easy with AI.
The value for managers is in being able to identify high-performing salespeople and accounts that are likely to be successful, meaning that they can refocus energy and resources to those parts of their business. This not only improves sales processes and pipeline management but also lends beneficial processes to HR departments and those monitoring team performance and allows for adjustments to be made to ensure a smoother way of working.
Freeing up time
AI is already having a major impact for sales and marketing teams, especially when it comes to lead generation, but as the technology progresses, there will be even more advantages to the reach it can make in the future.
The cumulative effect of applying AI and big data solutions is in freeing up time for human workers. While machines take over the mundane, repetitive, and analytical tasks that consume so much of our time, we are free to think more creatively and work more effectively.
How to Choose: Comparing 5 powerful sales automation platforms
A good example for B2B companies is the traditional sales rep. If AI can manage the 22% of a day spent searching for prospects or performing administrative task, then that’s a sizable chunk of his time that he can now be used to engage with clients and close more deals.
Advantages of AI in aftercare
It’s not just the sales and marketing process that is set to benefit from some degree of AI or data treatment, after all, a sale does not just end once a customer is on board as a client or has purchased a product.
This is one area where a lot of businesses are already using AI to improve their processes. The more common use of chatbots is enabling 24/7 customer support, talking with and guiding customers at all times of the day. AI can also gather data from customer interactions and provide valuable insight and analytics.
By providing a smoother and more convenient customer service experience, AI will further help to heighten customer happiness. This will inevitably keep retention rates steady and gives marketing teams plenty of material to work with through satisfied customer testimonials and referrals.
The future, therefore, isn’t one of robots taking over and replacing all human interaction and workplace responsibilities, rather the considered assistance that comes with properly-managed data and AI systems. There is a future out there to grab immediately, it’s knowing how it is applied that will place the early adopters front and centre.
Written by James Isilay, CEO of Cognism
Predictive analytics: good governance holds key to accurate forecasting