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Why you need a smart sales CRM?

Smart Automation using Artificial Intelligence
Smart CRM uses power of smart phone and AI

What is CRM? As per wiki “Customer relationship management(CRM) is an approach to managing a company’s interaction with current and potential customers, is one the best ways how you can do a combination in between accounting and business. It uses data analysis about customers’ history with a company to improve business relationships with customers, specifically focusing on customer retention and ultimately driving sales growth” wiki

In most of the CRM tools available today, sales people need to enter data and this data would be processed for meaningful strategic outcome. However, entering data manually comes with a cost. Data entry is costing your employees valuable time and energy, and the trend shows that this cost is just increasing. With today’s technology, the question could be asked if CRMs shouldn’t be more intelligent by now. Have a critical look at your sales organization and you’ll probably start seeing the leaks. Don’t allow this to eat your sales organization from the inside.

First of all, Sales employees to focus on sales, but you also need the data in your CRM to be able to manage your operations. Research has shown that the average employee using CRM tool spends about 4 hours per week entering data into the CRM system manually.

Secondly, imagine your employee who generated good sales, but doesn’t get paid out because the data hasn’t been entered properly. Shouldn’t this employee concentrate more on sales instead of spending time on entering data?

On average, only 40% of all sales updates are ever entered into a CRM. Again, the reasoning behind this is actually easy to understand. In addition, data is typically only entered at certain moments of the week or month. Either when a reminder is sent to enter the data, or shortly before a team meeting where results are being discussed. This means that only at specific moments will you have all information in your CRM to actually make good decisions.

And finally, what happens if a sales rep leaves the company? Typically, a large part of the pipeline simply goes up in smoke. Vanished, as if it was never there. You lose any progress made, and might even sabotage other sales reps who pick up those prospects and don’t know the history. All because the data wasn’t entered.

Why automation is the only solution?

The only real solution can be to take this work away from them. The 4+ hours per week spent on entering the data, and the time and energy spent on the discussion around it, can be saved by automating this process.

With advancement of technologies, it is possible to use latest technologies to automate most of the tasks. Here are couple of automation those can help to reduce the burden of manual data entry

Email automation – Email is the first communication channel to reach customer. The user should be notified when customer opens the email, entering data to the system when email received from customer. The system should notify the summary of emails received from customer with sentiment analysis. This will help sales people to further engage with customers in real time. This will help relieving sales employees of administrative work and support sales leaders in creating a high-performance sales organization.

Call Management – Imagine you are talking to customer and phone screen flashes with some visual clue to inform you the mood of the customer. Based on that you can decide how to talk to customers, whether is customer is interested or not. After the talk is over, the system should generate summary of the talk and also sentiment of discussion. This will help sales people to improve their communication skills as well. As the summary of talk is already stored in the system, further communication with customer will be more productive.

Geo-fencing – Geo-fencing is another feature to inform sales people of any nearby customers based on their movement and geo-distance. It is a virtual perimeter that allows users to see existing clients and leads on a map. For sales professionals with access to a geo-location tool in CRM, targeting and selling to a specific geographic area has never been more simple.

With advancement of technology, it’s now time for CRM+, CRM plus smart automation with intelligent data analysis.

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AI and Email text generation

81% of SMBs use email campaigns to nurture their audiences.

Email is the most important tool for any business communication. The key to great e-mail communication is crafting content that people actually want in their inboxes and that speaks to each customer separately, instead of a single e-mail sent to one and all. A badly written email, rather than speeding up communication, proposal or instruction slows down business processes. However generating a proper email content for any business discussion is a difficult task. It needs lots of experience and practice with multiple iteration. The future of e-mail is real-time, behavior-based personalization.

With advancement of AI related tools and methodologies, there are efforts to assist in email content generation. Can AI help or fully automate content generation? I would be covering couple of my experience on this subject.

Artificial intelligence (AI) and machine learning (ML) are fascinating in that they benefit every facet of content marketing. Specifically, through advanced machine learning technology, the process of creating content marketing strategies becomes easier.

Developing such systems have two types, one is static type of check typos, grammar and syntax and second type of a complete AI solution, an adaptive system to generate content based on a set of questionnaire.

There are tools, like browser plugin Grammarly to highlight any grammatical mistakes, tone of your email as you compose your emails. There is a javascript based SDK https://www.inboxsdk.com/ to be used for developing such mail plugins. You can use gmail plugin development framework for developing such mail plugins too.

Its AI everywhere and its time to use the power of AI and machine learning to assist in content generation for business. The very first step of a successful AI system depends upon the quality of training data set and methodology used.

Content of an email would be different based on the context – domain. Likewise, training data is also context dependent. Email training data set for finance domain is different than retail domain. There need to have a general training set and then domain specific training sets. User will be prompted with set of questionnaire to aid in text generation. Or user can enter a set of keywords – domain specific. Based on the user feedback, appropriate training set would be used, or a hybrid of multiple training set would be used to generate email content.

Recently google has introduced text suggestions in their gmail platform, when user types any sentence, the AI engine would prompt auto suggestion. It helps commonly used to words to complete the sentence.

There are some neural network based libraries to help in character level prediction like char-rnn – https://github.com/karpathy/char-rnn the model takes one text file as input and trains a Recurrent Neural Network that learns to predict the next character in a sequence. The RNN can then be used to generate text character by character that will look like the original training data.

https://github.com/jcjohnson/torch-rnn torch-rnn provides high-performance, reusable RNN and LSTM modules for torch7, and uses these modules for character-level language modeling similar to char-rnn.

There are some RNN – Recurrent neural network based text generation libarries like textgenrnn – https://github.com/minimaxir/textgenrnn – a library developed on top of Keras/TensorFlow , easy to train and can be integrated quickly. Then we come across OpenAI’s text generation framework https://openai.com/blog/gpt-2-1-5b-release/ , Gpt-2 from OpenAI is the most powerful text generation framework. OpenAI unveiled its new AI language system, GPT-2, and TalkToTransformer is a slimmed-down, accessible version of that same technology, which has been made accessible only to select scientists and journalists in the pastIn the beginning, it was not released completely with fear that it might be used for anti-social activities.

In a nutshell, AI based email text generation is a long way to go and there are some good libraries to help you. GPT-2 language modeling system from OpenAI would be the most innovative text generation system.

GPT-2 is a large transformer-based language model with 1.5 billion parameters, trained on a dataset of 8 million web pages. GPT-2 is trained with a simple objective: predict the next word, given all of the previous words within some text

Generating title of any email, especially business email is a tricky task. The very first thing User sees is the subject of email. There is a Neural Network based library NLU Email Title to help in email subject generation.