AI is here to stay. Have you upgraded?

AI is here to stay. Have you upgraded?

About five years back, the sales function was at a standstill, no new advancements were happening, and the sales rep carried on their business like routine. The CRMs were the last addition to their workflow, and even though CRMs have been adopted by over 75% of the companies today, the engagement, however, is still low. However, in the last five years, technology has taken a huge leap, and the repercussions are seen all across industries. Right from e-commerce to healthcare – technology has widespread applications. One such miraculous technological advancement is artificial intelligence. Artificial Intelligence has been able to revive many dust-covered functions, and one such function is sales. With the advent of AI in sales, sales reps have renewed ways of going about their daily activities. As per a PWC report, 55% people believe AI’s potential to boost business productivity, inform strategy and generate growth outweighs the potential downside of employment concerns.

Let’s look at Dave and how his life looks like with AI enabled systems:

1. Geo-tracking

Dave has three meetings lined today as per the leads allocated to him. He has to visit WCT office in the morning, the ACT office in the afternoon and GEN office after that. He checks his phone worried about making it in time to all these meetings and realized that all of them are barely 1-3 miles apart. His job becomes easy.

Dave’s manager was able to track his location and allocate leads in the same area to him cutting down his travel time.

2. Data Entry

Dave has a bunch of calls today in between his meetings and hasn’t had time to enter his activities in the CRM. He is already exhausted from all the meetings. He decides to take a look at his phone and realizes all his activities have already been logged in and set up.

He is glad he can head home early, and his manager is happy to receive all updates for the day.

3. Lead Management

Dave had been to an event a few days back where he managed to get business cards from a bunch of prospective clients. He takes his phone out scans them, and the data is fed automatically. He makes calls and emails a few. All of these are attributed to the lead along with the location. Based on past trends, he has a few suggestions on the future course of action to take with the leads.

He follows this and manages to save a hell lot of time which would have otherwise gone in research and figuring out what to do next.

4. Pipeline Management

One of the meetings Dave scheduled for the day has been canceled. Dave has a 3-hour gap in this calendar and wants to do something productive. His phone is all set to help him out. He has three meeting suggestions ready. He makes a couple of calls and schedules another meeting instantly.

5. Coaching & Goal Tracking

Dave didn’t always belong to the top quartile – he reached there with hard work and a bit of help from AI. AI has the capability to learn from user behavior and understand what is a top quartile rep doing differently. It reads the data captured by tracking activities and forms patterns. These patterns give rise to concrete suggestions which can help the reps from other quartiles to improve their performance.

6. Predictive Analytics

Dave’s manager is usually under a lot of stress when the sales review is nearing. He has to show numbers and forecast numbers for the next quarter. Moreover, he wants to be well prepared to present his wins and explains his loses. Doing this by himself takes a lot of time and the results are never as per what the management expects. However, his job is made easy by AI. He has in-depth reports about every aspect. He can establish trends and get his forecast in a matter of seconds, that too accurate till the last number.

The above 6 points cover only generic applications of Sales AI. In deeper, more industry-specific applications, solutions can be game-changing. AI is capable of accurately pinpointing and solving a business problem saving the firm millions of dollars today. Vymo has been successful in helping few industries by providing solutions which have helped solve unique problems. Take a look at these case studies:

Bioseed

Treebo

SBI Life Insurance

HDFC Bank

Few other issues, AI has been able to solve are:

Sales & Marketing Gap

In terms of sales and marketing funnels, the gap has been too wide and festering for too long. In an ideal scenario, the two functions should go hand in hand. But, in most cases, the two teams are completely unaware of what efforts the other is putting in. The way the incoming customers should flow is: Branding > Lead Generation > Sales > Customer Service. Each of these layers represents different teams. It is bound to cause some leakages in this entire funnel causing leads to drop off. This is where AI steps in and helps the workflow as a whole to function smoother.

Let’s take an example: a firm has each of the functions mentioned above. They use a system that helps them understand the overall impact of the entire funnel.

Branding keeps a keen eye on the industry trends, what people are looking for and where the stock market is moving. They choose from a wide range of trending topics to launch a brand campaign.

The search engines are buzzing, the impact is seen in organic brand searches, product searches and so on. The SEO improves and people land on the website organically, getting a good lead score.

This further impacts the lead generation campaigns by further dropping the CPC. Getting better rates than the competition. The lead further gets scored by clicking on a retargeted ad generated because of the website visit. The lead is warm enough to be passed on to sales.

The same AI engine responsible for scoring the lead, suggests the sales team an ideal course of action. A successful call, few meetings, email interactions and so on increase the score of the lead and the lead is closed and becomes a customer.

The same lead is passed on to customer service/post sales. The same AI services are able to segment queries and allocate better on the basis of specialty and bandwidth to ensure end-to-end satisfaction of a customer.

Hyper-Personalization

A sales rep may not remember what the customer asked for or what the customer was looking for last time she visited the website or what is the nature of the need the customer has. But, AI does. Take an example of an insurance website. A person comes on to the website and fills in details to calculate premium of life insurance and leaves the website. AI has the power to capture this data and show it in a retargeted ad across platforms. If she fills the lead form, the sales rep will have exact data about the need of the customer – without wasting time the rep can close the deal sooner.

Better Insights

One of the most elegant uses of AI is to use sophisticated machine learning algorithms for processing data as per the need and drive almost accurate insights out of it. The computer has the capability to calculate near perfect business forecasts and give suggestions on what can be done next. It can identify processes which are time-consuming and reallocate resources to optimize them.

The best part is, all of this can now be done in seconds! Right from giving consumer solutions to solving business problems – data can now help in every aspect.

Artificial intelligence has arrived and it is here to stay for the long haul. Have you upgraded yet?

Download the ebook: A day in the life of a sales rep to know how Vymo can help you optimize your sales process. 

A-day-in-the-life-of-Jane-smith_Sales-AI_ebook

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