We are living and competing in a data-driven world. Data is our newest natural resource–it is everywhere. It is no longer a question of how to access data, but how to effectively cultivate it. One of the most promising means of understanding data in an easily digestible way is Natural Language Processing (NLP).
NLP is a field of Artificial Intelligence (AI) that involves analyzing human speech and text, and deriving meaning from it. NLP continues to transform the ways in which businesses interact with their prospects and customers. Facebook, Google, Apple, and other technology giants are leveraging NLP to power everything from chatbots and virtual assistants to search results and personalized recommendations.
NLP-powered CRM platforms can move waters in terms of helping salespeople achieve their key sales objectives, including increased conversion rates, larger revenue numbers, and, most important, higher sales productivity levels.
Forward-thinking relationship management platforms are also starting to reap big benefits from NLP technology. NLP-powered CRMs are able to surface key insights about prospects and customers and fuel sales effectiveness.
Eliminating Manual Data Entry
Nearly 1/4 (23%) of salespeople cite manual data entry as the biggest challenge associated with using their existing CRM solutions. With thousands of contact records in a typical CRM system, the time required to input and update records is colossal. According to Hubspot, one-third (32%) of salespeople spend an hour or more on data entry each day.
NLP liberates salespeople from squandering valuable time on manual CRM data entry.
NLP technology can extract contact data (such as individual and company names, email addresses, phone numbers, and physical addresses) from customer emails, support requests, social media profiles, or other platforms and automatically populate contact records in CRM systems. When teams leverage technology to do manual routine work like CRM data entry, their salespeople are able to devote proportionally more resources to building real relationships with their prospects and customers.
Predicting Buying Propensity
Salespeople frequently struggle to accurately predict customers’ buying propensities. The lack of predictive power results in them focusing valuable time of leads that offer a little potential for conversion. It’s no wonder that today a mere 22% of salespeople are satisfied with their lead conversion rates.
NLP can assist salespeople in predicting customers’ buying propensities for their products and services. Customers use different words, phrases, and sentence structures at different stages of the buying cycle. Whereas, they tend to use interrogatives such as “who”, “what”, and “why” in the early stages, they tend to use verbs such as “purchase”,“become”,“guarantee”, and “discuss” in later stages.
NLP can process email and other customer communications and gauge whether a given prospect is truly interested in an offering and if he/she is ready to purchase.
Prioritizing Incoming Requests
It can be very difficult for businesses to prioritize customer service and support inquiries from prospects and customers. With NLP, salespeople are able to discern the nature of an incoming request, without needing to read it. NLP technology has the capability to scan requests and determine, with a high level of accuracy, the underlying tone, intent, and degree of urgency. For example, requests that contain jargon such as “frustrated”, “doesn’t work”, “broken”, and “competitor” are likely more urgent and time-sensitive than requests that contain jargon such as “great”, “superior”, and “best”.
Now companies can run sentiment analysis on text data to expedite ticketing. It aids sales and customer success in prioritizing the most time-sensitive queries. It also highlights the customer’s emotional state, enabling sales and CS to ameliorate and resolve critical customer issues before they wreak long-term havoc on a business.
Gauging Customer Satisfaction Levels
Using sentiment analysis, NLP technology is able to process and decipher structured and free text contained in customer testimonials, surveys, emails, social media posts, etc. and classify keywords and phrases according to whether they infer positive, neutral, or negative sentiments. The implications of sentiment analysis capabilities are transformative in terms of helping salespeople accurately gauge customers’ tones and overall levels of satisfaction with offerings.
Is the customer frustrated with the brand? Does the customer regret his/her purchase? Is the customer delighted with his/her purchase? Have customer sentiments changed over time?
It’s game-changing when customer satisfaction information gleaned from NLP is automatically inputted into a CRM system for salespeople to closely monitor. For example, workflows can then be set up that automatically prompt salesperson to reach out to unsatisfied customers and attempt to remedy the situation.
Additionally, workflows can also be set up that prompt salesperson to proactively reach out to satisfied customers and engage in up-sell and cross-sell conversations, with the knowledge that satisfied customers are most likely to entertain these conversations.
Determining Relationship Strengths
At the end of the day, the ultimate objective of CRM platforms is to assess the strength of a firm’s relationships with prospects and customers. Relationship scores are incredibly valuable when trying to discover a path to referral or introduction to a prospect or potential partner. Often there is a stark difference between an individual who has a connection on LinkedIn, Facebook or Twitter and someone who exhibits a 90% relationship score on Affinity. As social media becomes more prevalent and relevant, we are destined to see a weakening in terms of the strengths of some of our social media relationships.
As Robin Dunbar famously stated in Dunbar’s Number, there is a cognitive limit, roughly 150 individuals, associated with the number of individuals with whom one can maintain stable social relationships. Superficial social media connections give the illusion that our relationship number is increasing, but, in reality, these relationships only grow and fortify with real 1-to-1 human interactions. Platforms such as Affinity help leaders foster and keep track of relationships so that they can be effectively leveraged in the future.
CRM systems have been in existence for decades. While CRM systems have stood the test of time thus far, they are in dire need of a makeover. NLP-powered CRM platforms can move waters in terms of helping salespeople achieve their key sales objectives, including increased conversion rates, larger revenue numbers, and, most important, higher sales productivity levels.