Augmented Lead Scoring

Improving lead conversion is a direct multiplier of revenue. There is no better way than machine learning to rank your leads by likelihood to convert, so you can focus sales and marketing on the prospects that matter most.
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Background

Improving lead conversion is critical to business success, and small changes can make an enormous difference in your bottom line. The average website converts at around 2.3%, while the best websites convert at 11% or more. There are similar metrics for sales teams.

At the same time, statistics indicate that companies spend just $1 on conversion rate optimization for every $92 spent on customer acquisition. Ideally, you’ll put just as much focus on lead conversion as lead generation, as gaining just 100 leads with a rock-solid 10% conversion rate is the same as gaining 1,000 leads with a middling 1% conversion rate. Ignoring lead conversion means that your sales and marketing efforts will be an uphill battle.

In that sense, improving lead conversion is a direct multiplier of revenue. There’s no better way than machine learning to rank your leads by likelihood to convert, so you can focus sales and marketing on the prospects that matter most.

With Akkio’s no-code machine learning, you can easily build and deploy augmented lead scoring models, and improve your bottom line.

Augmented Lead Scoring With AI

To get started, sign up to Akkio for free. As with any machine learning task, the first step is getting historical data and picking a column to predict.

Historical Data

In our video tutorial, the historical data is 41,188 leads with descriptive attributes like age, job, marital status, and educational status. The file includes a target variable called “subscribed.”

We can use machine learning to calculate the probability that a customer subscribed to an offer, and then prioritize leads with a high probability of subscribing.

This dataset is already uploaded to Akkio for demonstration purposes, which you can see on the homepage as “Lead Scoring Demo,” but you can upload any dataset you want by simply clicking “Upload Dataset.”

Below, we’ll explore how to connect Salesforce to Akkio. First, we simply create a new flow, and connect our Salesforce account.

A screenshot of the Akkio Flow with Salesforce highlighted as a primary input.

Note that, to connect Akkio with Salesforce, you need a Salesforce Edition with API access, which can be Enterprise, Unlimited, Developer, or Performance. The Group, Essentials, and Professional Editions do not have API access.

If you don’t already have a relevant Salesforce account, you can sign up for a Salesforce Developer Trial, which includes example datasets, such as “opportunity.csv,” which we’ll use below to predict the probability of a lead being won.

A screenshot of the Akkio Flow with a Salesforce dataset connected as the input.

Building the Model

Now, we can click on the second step in the AI flow, which is “Predict.” Under “predict fields” you can select the column to predict, named “Won.”

A screenshot of the Akkio Flow in the second step, where the user can create a predictive model.

Then just hit “Create Predictive Model,” and you’re done! In the lead scoring demo, the model has already been made, but it takes as little as 10 seconds to train a model from scratch. You can also select a longer training time—from 1 to 5 minutes—for potentially more accurate models. Keep in mind that longer training times will not always necessarily perform better.

Also note that you don’t pay for model training time, unlike with many typical automated machine learning tools, so feel free to build as many models as you’d like.

Analyzing the Model

After a model is created, you get a simple overview, which highlights the top fields, model prediction quality, sample predictions, and more.

A screenshot of an Akkio AI model report that predicts sales wins.

There’s also the option to “See Model Report,” which lets us easily collaborate with others and share these model details with anyone, even if they don’t have an Akkio account.

In short, we’ve discovered that it’s very easy to build a highly accurate model to score leads.

Deploying the Model

Now that we’ve built a model, it’s time to deploy it in the real-world.

With Akkio, it becomes trivial to deploy complex machine learning models. The lead scoring demo shows deployment via web app as the third step, which is an easy way to instantly serve predictions. It’s also possible to deploy through Salesforce, Google Sheets, Snowflake, and the Akkio API, with many more methods coming soon.

Further, you could deploy the model in practically any setting with Zapier, a no-code automation tool that connects tools with “Zaps.” Zapier allows you to link up thousands of different tools, so no matter where your data is coming from, it’s easy to connect it to Akkio to get a prediction, even if you don’t have any technical expertise.

If you’re looking for more technical power, you can also use Akkio’s API, which is formatted as a Curl command, allowing you to send a GET request that contains your flow key, API key, and input data, and get a prediction back.

Since we’ve made predictions based off of Salesforce data, let’s deploy our model back in Salesforce as well, and update our Salesforce data with our predictions. Simply add a third step, and select Salesforce as the output. From there, configure your output settings according to the desired schedule, run rules, and so on.

A screenshot of an Akkio Flow in the third step, where the user is configuring deployment settings for Salesforce.

And you’re done! Once you’ve filled in the desired configuration, simply hit “Deploy,” and you’ll have a live AI model making predictions on Salesforce data.

Summary

We’ve explored how increasing conversion rates can be a key driver of business success. If you’re only focused on lead generation and not lead conversion, you’re leaving money on the table. Highly successful landing pages and sales teams convert upwards of 10% of their leads, which makes their lead generation efforts much more fruitful.

Using Akkio’s no-code AI, you can effortlessly build and deploy lead scoring models, and operate more effective sales and marketing teams.

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