A huge number of new AI technologies have sprung up in the past couple of years. They have a promise of improving specific areas much more than other technologies had done before. We think of AI as one step above automation technologies.
Past couple of decades were all about automation. Automation provided a major boost to execution efficiency metrics and improved revenues. Today, it’s increasingly about applying intelligence to each of these processes. This is done by generating and storing data at various decision points (process nodes).
This data is of two kinds:
- Old decision data (effectiveness score model is based on activities post decision date)
- Algorithms that generate prioritised decisions
Automated processes get a boost because of the high quality decision data available to automation engines. These sophisticated automations running through process points where the need of high quality decisions is now satisfied at a much more rapid pace boosts business productivity to new levels.
Eyes and ears are key data collection mechanisms to help the human brain take decisions. Previous experiences, which we call decision data, help a human brain to take the right actions fast.
A functional business example can help better understand it.
Sales and Marketing function is key function to any business. It starts with visitors coming to websites or events through lead generation activities. Those visitors are qualified by marketing teams to mark them as leads. These leads are nurtured by inside sales teams to qualify or disqualify them based on certain scoring criteria. This gives an early indication of whether the lead can be helped by any of the companies current offerings or not. Qualified leads are processed by sales teams for connecting the requirement with a given offering, scoping the work, providing a technical validation to the prospect followed with a proposal and then the account is marked as closed won or closed lost based on the final negotiations and pricing discussions.
Applying AI to above function is done by looking into each of the following questions:
- Are there better ways to have targeted accounts so that the demand generation team focuses on selected few accounts instead spray and pray? Do tools like discoverorg provide intelligent algorithms where one can search for “Accounts LIKE my top 10 happy customers” And get a list of accounts that matches various parameters of size, type of industry etc. And provides smaller list for targeting with a higher probability of closing with references from happy customers. Usage of these intelligent algorithms on traditional data can make a world of difference in speed and cost of demand generation.
- New age tools like Bombora tells us what people are searching for in a given account. Bombora calls out key phrases that are trending up within that account, so that marketing teams can approach people who are looking for help instead of marketing trying to find out who needs help. This can further narrow down and target leads effectively.
- 77% leads are dropped in lead nurturing activities as cold or warm leads and teams run behind setting up new events without processing leads from earlier events. Using AI Assistant tools like 7Targets helps process 100% of the leads diligently without grammatical mistakes using natural language generation and natural language processing. This has proven to get a few more meetings and generate more revenue increasing ROI of sales and marketing spends.
- Knowledge graphs and intent based chatbots have helped prospects to instantly get answers from businesses within seconds. Similar queries resulted in delayed processing and sometimes drop in leads when these technologies were not available. Delay in response increases the chances of losing the opportunity greatly.
- A few sales people tend to sell much better than other sales team members within the same geo and in the same quarter. Several AI tools help to uncover the phrases used by sales people who sell better. These tools also analyse aspects such as ‘number of pauses’ a salesperson uses to not make sales meetings a monologue. These pauses and phrases are then used by other sales team members to enable them like never before in effective selling.
The above example was to help give a quick glimpse of how AI techniques can be applied over several areas across a marketing and sales function to improve the throughput along every aspect of the pipeline.
Our company, Applied AI consultants helps in assessing current state and adding the required Cloud and IoT technologies to gather more data and feeding them into AI tools based automation pipelines to get significant processing power that is repeatable and consistent resulting in high quality outcome.