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What is Predictive Lead Scoring and How Can It Help You?

One of the most common struggles faced by sales professionals is sifting through countless leads for finding which one is actually worth pursuing at the end. An effective solution that solves this problem at hand is called predictive lead scoring

With the use of predictive lead scoring, it is possible to streamline the lead-scoring process while focusing on promising prospects for improved conversions. A good predictive lead scoring software can use historical patterns and behaviors for predicting a lead’s conversion chance using data and analytics.

In this blog, we will explore the possible benefits and importance of predictive lead scoring and how it can help in prioritizing efforts and driving revenue growth. To begin with, let us begin by understanding what is predictive lead scoring. 

What is Predictive Lead Scoring?

Predictive lead scoring is the process that is used in sales and marketing for finding which leads have a high chance of becoming well-paying customers in the future. All leads take a numerical value or ranking based on specific behaviors, characteristics, and interactions on a website, social media platforms, email campaigns, and other touch points.

The common predictive lead scoring algorithm also considers different variables that can suggest a lead’s common probability to convert while including demographic data, size of the company, job title, degree of interaction with the company website, and past purchases. 

The sales and marketing teams can focus all of their efforts and resources on all promising leads by employing the predictive lead scoring process which eventually helps in boosting the effectiveness of the outreach and also helps in increasing the conversion rates. This is a method that can help businesses in finding where their lead generation and marketing strategies need work.

To understand this a little better, let us talk with examples. Think of two leads called X and Y. On the basis of their behavior and other rules set important for a firm, Lead X may have 60 points based on the predictive lead scoring method while Lead Y may have 30 points. This rating is descriptive of the fact that lead X has more chances of getting converted in the future. However, this does not mean that you ignore lead Y. After you are done converting lead X, you can now look at the probable factors affecting the low score of lead Y and develop a plan to increase its ratings. 

Why Should Companies Use Predictive Lead Scoring?

There are many reasons why you should adopt predictive lead scoring in business development. We will mention them below one by one. 

Why Should Companies Use Predictive Lead Scoring


1. Improved Lead Targeting

Predictive lead scoring is a process that helps in finding which leads can be converted easily. It enables you to focus on resources that have maximum potential. It is possible to improve the lead conversion rates and also increase sales by targeting your efforts effectively

2. Lead Qualification

The process of predictive lead scoring also helps in automating a significant portion of the lead qualification process along with saving time and effort by finding all high-potential prospects. The sales and marketing teams can become increasingly effective which then frees them up to take up more work and get other essential tasks done.

3. Customer Experience

Predictive lead scoring also ensures that you deliver a much more personalized and relevant customer experience by customizing your messaging and offers to specific needs and interests. You can customize the customer experience and build a rather stronger relationship with customers while also increasing their loyalty to your brand.

3. Data-Driven Valuable Insights

With a detailed analysis of the data used in predictive lead scoring, you can gain important insights about customer behavior and preferences. Moreover, you can also understand your customers so that the marketing and sales strategies are improved eventually and new growth opportunities are discovered. 

4. Competitive Edge

With the help of predictive lead scoring, you can effectively gain a competitive edge because it helps in identifying and converting high-potential leads quickly as compared to competitors. Gaining this edge can help you in gaining more profitability and grow your market share as well. 

Importance of Predictive Lead Scoring

Businesses can effectively profit much more than the combination of human intuition and machine learning algorithms. This can be successful in the predictive lead scores. Some of the reasons why predictive lead scoring help are mentioned below. 

1. Work With Data-Driven Insights

Let’s take an example of predictive lead scoring in the sense of a functional e-commerce website. When you track a user’s behavior on the website including the visited pages, products seen, and items added to the cart, the website finds it easy to score all users for making a purchase. 

It is also possible to personalize the user experience with lead scores by offering discounts and suggesting products that are relevant to their interests. Predictive lead scoring does an excellent job of making data-driven decisions that can improve the effectiveness of marketing and sales efforts which then results in better revenue. 

Data precision insights into the potential value of all leads or users enable businesses to allocate their resources effectively and focus more on growth opportunities. 

2. Saves More Time

The lead scoring process is important for all successful sales teams but the conventional approach of manual scoring can be time-consuming and also prone to human errors. With predictive lead scoring, improved methods of data consolidation from different sources can offer quick and accurate results. 

Predictive lead scoring can save the sales team and also allow it to focus on higher-value tasks including engaging with qualified leads. In addition, the automation of lead scoring can also effective reduce all risks of human errors. 

While being dependent on manual scoring, you can often miss out on significant details and sometimes even misjudge the quality of a lead. However, with automated scoring, this algorithm follows predefined rules making sure that all leads are evaluated without any bias. 

3. Sales and Marketing Symbiosis

The importance of good communication between a company’s sales and marketing departments must never be doubted. When the teams collaborate well, they can effectively develop a robust strategy that can also promote further development.

Moreover, sales and marketing teams can also work together for defining requirements that can be used for scoring leads. Aligning the teams with lead score criteria makes sure that teams are in proper sync on qualified leads and the data that should be considered. 

4. Sharing Data

The teams can effectively share collected data for getting precise predictions that can further be helpful for making important decisions. 

Marketing can offer data including website traffic, social media engagement, and email opening rates while sales can offer important data including deal size, closing rates, etc.

5. Monitor and Change The Process

The sales and marketing teams can also consistently monitor the lead scoring process for ensuring that everything works effectively. 

You can track the process and include the accuracy of predictions, find possible areas for improvement, and also adjust scoring criteria just as required. 

Improve Your Sales and Marketing Efforts With Predictive Lead Scoring

Predictive lead scoring provides many benefits for businesses that wish to improve their sales and marketing efforts cumulatively. They come with peculiar benefits for both the sales and marketing teams. Let’s look at these benefits below. 

Improve Your Sales and Marketing Efforts With Predictive Lead Scoring

Sales Team

The importance of lead scoring is such that it enables you to prioritize leads based on their likelihood to get converted. You can target leads based on this which further means that sales representatives can focus more on engaging with leads to become customers rather than wasting time on low-quality leads. 

The sales teams can also customize the outreach to specific leads by using the benefits of predictive lead scoring. Some ways in which this can be done include customizing messaging, offering targeted promotions, and providing specific product recommendations. 

Predictive lead scoring also helps in offering insights into where the leads are in the sales funnel and how they can be optimized further. For instance, in case a specific stage of the funnel is causing the leads to drop off then the team can focus on improving the lead conversion process. 

Finally, predictive lead scoring software offers a measurable way to evaluate the success of a sales team. You can track conversion rates of leads with many different scores while gaining insights into what is working and what is not so that you can adjust this approach accordingly. 

Related Read: Grow Sales With Effective Lead Management

Marketing Teams

The predictive lead scoring software can also offer insights into which marketing campaigns and channels are effective for generating high-quality leads. Obtaining the insights helps marketing teams to streamline strategies and allocate resources accordingly. 

In addition, predictive lead scoring is also an extremely powerful tool for marketing teams to increase efficiency, improve lead quality, and ensure more revenue. You can leverage predictive lead-scoring software for achieving better results and staying ahead of the competition. 

Related Read: Best Digital Marketing Strategies for Lead Generation

Choosing a Perfect Predictive Lead Scoring Software

The process of choosing the right predictive lead-scoring software for a business is important because it includes many different aspects. You should identify all features you want to have in a predictive lead-scoring software, shortlist them and choose the ones you want finally. Check out these features and the accuracy they present by reading more reviews and case studies. 

Some factors that you must keep in mind while choosing the right lead-scoring software are mentioned below. 

1. Integration

The software must integrate with the present marketing automation and customer relationship management system. Remember that it is necessary for this software to go with the present data systems so that you can effectively analyze data and also offer accurate predictions. 

2. User Friendly

It is important to choose a predictive lead scoring software that can be user-friendly and also can be integrated into the sales and marketing workflows effectively. The software must be intuitive and offer actionable insights as well.

3. Customization

It is necessary to choose software that enables customization for meeting unique needs. This also includes lead scoring models and adjusting weights for reflecting the importance of different data points.

4. Customer Support

Remember to choose a predictive lead scoring software that is capable of offering dependable and responsive customer support at all times. The vendor should be able to offer access to training resources, a support team, and documentation so that you can troubleshoot any problems.

5.Cost

Finally, make sure that the software’s price is considered and that it fits your budget properly. You should check for software that is capable of offering a reasonable price with features that are needed and also avoid overspending on features that are not required. 

Zoho SalesIQ – The Best Predictive Lead Scoring Software

Zoho’s SalesIQ offers all these features with advanced AI algorithms, customizable models, seamless integrations with other applications, and also real-time scoring which makes it a renowned choice among businesses. It also comes with features to help businesses engage with website visitors, find high-quality leads, and convert them into customers.

Some of the features that this software offers are:

1. Customizable Lead Scoring Models

Zoho SalesIQ enables businesses to create custom lead scoring models that can reflect unique business needs. This includes adjusting the scoring criteria for reflecting the importance of different factors.

2. Advanced Lead Scoring

Zoho SalesIQ also uses advanced algorithms for predicting the likelihood of a lead converting into a customer. It helps businesses to prioritize high-quality leads and focus more on sales and marketing efforts. 

3. Website Visitor Tracking

You can get information on website visitors including their location, pages visited, and the time that they spend on the site. 

4. Marketing Automation

Zoho SalesIQ helps in combining marketing automation for prioritizing leads, personalizing campaigns, optimizing spending, automating leads, and improving sales coordination. It also integrates effectively with Zoho CRM and other CRM systems for tracking leads and managing customer data.

5. Cost Effective

Zoho SalesIQ also offers affordable and transparent pricing plans suitable for businesses of all sizes while making it accessible to small and medium-sized businesses. 

Empower Your Sales with Zoho SalesIQ’s Predictive Lead Scoring

In case your marketing and sales teams have been facing challenges with finding top leads while being unable to follow up with everyone predictive lead scoring is what your company needs.

Zoho SalesIQ can help you with the best predictive lead scoring with the aim to improve the revenue of your company significantly. Get in touch with our consultants at Encaptechno to know more about implementing the Zoho SalesIQ and use the best of what Zoho SalesIQ has to offer.

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How are AI Chatbots Revolutionizing Customer Support? | Encaptechno

How are AI Chatbots Revolutionizing Customer Support?

How are AI Chatbots Revolutionizing Customer Support? | Encaptechno


Artificial intelligence and all its possible implications can no longer be ignored. The suitable use of AI services and programs can potentially revolutionise a business like never before. The evolved companies are using AI for automating even the most basic tasks, changing interactions, building relationships, deriving profits, and offering services.

Artificial intelligence has also improved customer experience with personalised communication, image recognition, chatbots, and other recommendations. Most businesses use AI to enhance and personalise customer experiences. AI has a beneficial influence on customer success operations with the use of chatbots.

In fact, it has turned out that for earning the confidence and commitment of customers, AI-based chatbots have become critical. In this blog, we will try and understand how AI chatbots are changing customer support. Read on to know more.

What is a Chatbot?


What is a Chatbot?
A chatbot is computer software that helps businesses to automate conversations with customers. It is an artificial intelligence program that is designed to stimulate communications with customers. The customers can easily engage with an
AI-based chatbot through the chat window, messaging and voice applications.

Everyone in the present world has come across a chatbot whether they know it or not. For some time now, chatbots have done an exceptional job of replacing the humans from one end of the conversation and have enabled human to machine interactions.

The thing with chatbots is that they can process data for responding to all kinds of needs powered by AI, NLP, and machine learning. In case the chatbots cannot answer a question or a request, the chat transfers to a human agent.

Mainly, there are two types of chatbots: Flow chatbots and AI chatbots. Both of them are designed to improve customer experience. Flow chatbots are like tree-based models which mean that the user is guided down a predetermined path defined by a developer.

The AI-based chatbots are self-trained so they can produce backlogs of knowledge according to the information they receive by interacting with customers. Multiple online customer service platforms use chatbots to manage the volume of questions, phone calls, and other requests.

Modern Chatbots Meet Customer Expectations


The technological developments that we see around us are in one way or another meant to be like human body developments. Chatbots were originally developed to replace human conversations with a machine. However, there was a lot of scope for improvement.

In the past, the chatbots took anywhere between nine to twelve months to build and get deployed. The cost of a large number of experts and chatbot dedicated software engineers required the first generation chatbots to be less cost-optimal than they could be.

Other than this, the chatbots also did not offer better customer experience. The robotic chatbots were scripted and they could not foresee user intent or engage in a meaningful and dynamic dialogue. User interaction suffered immensely because of this which eventually affected the overall user experience.

There was also a lack of understanding in the earlier chatbots for meeting the rising user expectations. They could not find the want of the users and they could also not formulate specific and personalised responses.

Changes in Customer Support Experience


A core principle of selling is the ability to strike suitable conversations. In the past, one on one human interactions were used to answer questions and address all the questions. However, with the evolution of online platforms, the feature of 24×7 customer support becomes ever-present. To fulfil this need, chatbots were developed. These chatbots are cost-effective and offer support at all times.

Traditional chatbots revolutionised the concept of customer engagement beyond measure. They recognized keywords but failed to recognize the context in which they were being used. These chatbots did not have the ability to understand human emotions such as anger, frustration, etc. They also did not understand the way people speak.

Even though the development of chatbots was efficient, they were mechanical in nature. On the other hand, the demand for personalised conversations was gaining attention to offer a seamless customer experience. This is how AI-based chatbots came into being. In addition to quick and affordable solutions, these chatbots understood the context and intent of customers before doing anything meaningful.

The chatbots recognized customer frustration and switched the changes to a human in the company’s support centre. AI chatbots offer a personalised customer experience by providing customer data to the agents in real-time. It was realised that customers want quick, and frictionless solutions to their problems and so, AI-based chatbots were introduced to make this happen. Zobot and Salesforce Einstein Bots are perfect examples of this.

Why are Chatbots Important for a Business?


Chatbots provide a quick and engaging customer experience with troubleshooting services, a help desk, and an assistant at all times. Chatbots are more convenient and it takes lesser time for customers to strike conversations using them. A bot uses AI to search through sizeable quantities of information while accurately selecting relevant answers for a consumer.

It has been noted that businesses that use chatbots can reduce conventional tasks while also handling different requests from customers. This quick way of handling customer questions and offering constant support helps businesses to improve customer loyalty. Some of the benefits of chatbots are mentioned below:

1. Reduction in Turnaround Time 


It is challenging for businesses to maintain a balance between inbound customer queries and support agents. This is even if the company has a talented workforce and an agent is made responsible for handling only one customer at a time.

Manual tending to the customers leads to an increase in waiting time for customers due to which the business might lose a potential lead. On the other hand, chatbots have no such constraints. The implementation of AI-based chatbots can handle any number of customers and it can do this suitably.

2. Constant Customer Service and Support

Constant Customer Service and Support
The chatbots are capable of offering constant support to the customers. They use past conversations to improve at each stage.

The AI-based chatbots also enable everyone to offer at least the basic support needed for guiding a user to a specific section of the website while providing pricing details, etc.

3. Customer Needs


No matter which sector a business may operate in, it usually has a wide range of customer data needs including past transcripts of conversations, transaction history, etc. This is the data that is mostly unstructured because of which many companies fail when it comes to leveraging it.

The AI-based chatbots come with the ability to use this data for understanding the past and future requirements. It also helps the customers in receiving important information without manual intervention.

4. Omnichannel Experience


All businesses are needed to offer a
better customer experience if they wish to grow in the market. In fact, this is what makes a business stand out. It can be difficult for agents to juggle between platforms for offering customer support in real-time.

On the other hand, AI-based chatbots are capable of offering an omnichannel experience with easy integration. Different platforms can also be integrated with chatbots. No matter which channels your customer needs, the business is always ready to offer it.

5. Personalised Recommendations


Artificial Intelligence assists the customers in the form of customer purchasing decisions and the creation of suggestions based on those findings. The suggestions also aid in the creation of focused branding and marketing initiatives that increase customer interest.

It must be noted that most online buyers believe that it is easy to obtain reliable and efficient suggestions using the power of AI and machine learning. The manual data can be used by AI to analyse purchasing trends and do predictive and prescriptive analyses to increase engagement.

AI discovers methods for shaping and creating a better customer experience interaction. Common opportunities such as upselling and cross-selling have the ability to increase because of improved suggestions.

6. Efficient Services


Efficient Services
We have already understood in the points mentioned above that customers want rapid and efficient services which is something that should not be overlooked. AI-based chatbots satisfy this consistently and efficiently.

The chatbots have few mistakes which make it easy for customers to obtain the information that is needed for improving their analytical abilities. Customer service can either make or break a business because it must be responsive, consistent, and focused. 

Chatbots for example can answer simple questions, minimise touchpoints, expedite conversations and assist with complicated situations. AI-powered virtual assistants aid consumers in navigating the procedure and conversing with them. Natural language processing, voice assistants, and machine learning can allow AI agents to make it easy to approach customers online.

7. Real-Time Decision Making


Organisations may also employ tracking and data analytics for interacting with the customers on a deeper level because of technologies like artificial intelligence and
machine learning. Other than this, facial expressions can also be taken into account for allowing a personalised and tailored customer experience.

The AI technologies also help in data cleaning, merging, and rearranging helps in making quick decisions. Other than this customer feedback, service requests, and response times can also be improved. The AI technology can be used for extracting customer trends and customer interactions.

With the real-time data, visual analysis and personal engagement with customers also improves considerably. The information used helps in providing excellent customer support along with fostering deeper relationships.

8. Better Product Recommendations


The teams can use AI-driven suggestions for offering the best products recommendations by combining the data and knowledge together. It is also possible to improve sales by collecting data such as website search questions, purchase habits and so on.

The suggestions have the ability to offer the best product characteristics and dynamic data. With the media initiatives, product suggestions can also lead to a better customer experience. The customers can learn more about the items they have purchased while locating comparable ones that can improve their experience.

Product suggestions also help in determining which aspects of a product such as composition, performance, scope, and function can be improved. This increases the overall product characteristics while also improving the core emphasis on products and services.

Conclusion


To make sure that the customer information is used successfully, data is important for ensuring the best customer experience. All customers must be served by an AI-based customer support centre and AI solutions are an excellent way to do that. Companies must integrate this technology at the earliest.

More and more businesses are focusing on improving the customer experience for gaining loyalty and confidence. Great outcomes are possible if data-driven marketing innovations are used as a part of the marketing plan.

With the integration of customer data, AI is evolving to offer many options for customers including the creation of customer journey maps, reducing turnaround times, simplifying customer interactions, and increasing customer engagements. Making sure that these aspects are integrated will ensure user-friendly customer support and experience.

How are AI Chatbots Revolutionizing Customer Support? Read More »

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