Top 4 CRM AI Use Cases RevOps 10 min 91% of companies with more than 11 employees use Customer Relationship Management (CRM). However, only 12% of them actually use an AI-powered CRM tool! A lot of users believe that AI in CRM is still in the future and the current processes don’t require automation. But is this the case? What is an AI-powered CRM, and what are its use cases? Can businesses realize real benefit by using AI in their CRM? If so, what are the processes they can automate? We discuss all this, and a lot more in this detailed blog post. Read on. What is AI in CRM? CRM manages and maintains relationships with customers, prospects, and other business contacts. AI in CRM refers to integrating AI technologies into CRM software and processes to enhance customer interactions and improve business outcomes. AI in CRM enables businesses to analyze vast amounts of customer data, predict customer behavior, automate tasks, and personalize customer experiences. It empowers companies to deliver more targeted marketing, provide proactive customer support, and make data-driven decisions, ultimately leading to better customer satisfaction and increased sales. Why is AI required in CRM in 2025? In the modern business world, organizations require AI due to the following reasons: 1. Increasing unstructured data As the number of transactions grows, so does the volume of customer data. While this presents an opportunity for businesses to gain deeper insights into their customers, it also poses the challenge of managing and extracting relevant information from the predominantly unstructured data. However, AI tools offer a solution by converting unstructured data, which accounts for approximately 90% of the total data, into structured data, enabling businesses to leverage valuable information effectively. 2. Complex processes and relationships In addition to the expanding data volume, the rise in transactions leads to more intricate business processes and relationships. This complexity hinders a clear understanding of company relationships and accurate analysis of customer patterns. According to Xant, sales representatives spend over half of their time within CRM attempting to manage tasks more efficiently. AI technology presents a solution to this challenge by automating many of these tasks and providing valuable insights. By understanding customer sentiments, businesses can promptly address issues, improve their offerings, and enhance overall customer satisfaction. Benefits of AI-powered CRM Let’s have a detailed look at the benefits of AI-powered CRM. 1. Clean CRM data AI can help you achieve comprehensive contact lists for each account in your CRM by extracting them from your representatives’ email inboxes, calendars, and Zoom meetings. You can precisely categorize Account contacts and Opportunity Contact Roles (OCR) based on their engagement and relevance to ongoing Opportunities. AI can also automatically enhance each contact with updated job titles and phone numbers that remain up-to-date whenever changes occur. 2. Qualified pipeline Detect the absence of pre-engaged contacts or leads within the CRM. Conduct campaigns targeting GDPR-compliant contacts to expand the pipeline and expedite sales cycles, and identify contact roles to enhance targeted outreach efforts. 3. Tech Stack Audit Deep dive into the existing tools that your company is using. Identify all redundancies, and find opportunities to streamline the entire tech stack. i. Map Out Tools Compile a list of all tools used by teams, noting their purpose and how they work with the CRM. ii. Evaluate Use and Cost Determine if tools are actively used or if there are duplicates. Look for cost-saving opportunities by consolidating tools when possible.   3. Supercharged ABM You can recover inactive and lost deals and impact ongoing opportunities by employing Account-based Marketing (ABM) campaigns with current first-party buyer contacts directly sourced from sellers’ email inboxes and calendars. Increase funnel conversions by precisely targeting buyers through deep insights into buyer engagement within high-priority accounts, their buying roles, and the current sales stage of each account. 4. Data analysis and insights AI can allow you to process and analyze vast amounts of customer data to identify patterns, trends, and customer preferences, allowing businesses to make data-driven decisions. 5. Predictive analytics AI algorithms can predict customer behavior, such as identifying potential churn or predicting purchase intent, helping businesses proactively address customer needs. 6. Sentiment analysis AI can analyze customer sentiments from various sources, such as social media and surveys, helping companies understand customer satisfaction levels and identify potential issues. 7. Lead scoring and nurturing Assess and prioritize leads based on their likelihood to convert, optimizing sales efforts and increasing conversion rates. 8. Personalization AI Customer Relationship Management (CRM) systems have the capacity to customize customer engagements through the examination of valuable customer information like previous buying patterns, online activities, and demographic details. Subsequently, this data can be utilized to personalize marketing communications, suggest products, and facilitate customer support interactions, catering to the distinctive requirements and preferences of each individual customer. 9. Chatbots Chatbots can deliver immediate customer support, thereby enhancing response times. These chatbots are capable of addressing common inquiries, offering product suggestions, and handling uncomplicated transactions. Consequently, this expedites the overall process and allows human agents to concentrate on more intricate and demanding matters. 10. Omnichannel presence AI-driven CRMs have the capability to deliver smooth and uninterrupted customer support through various communication channels, including email, social media, chat, and phone. This enables customers to interact with businesses through their preferred means, leading to enhanced engagement and satisfaction. 11. Sales forecasting and performance analysis CRM can analyze historical sales data, market trends, and external factors to predict future sales performance accurately. This enables businesses to make informed decisions, allocate resources efficiently, and set realistic sales targets for their teams. 12. Churn Prediction and Customer Retention AI can analyze customer behavior and historical data to predict the likelihood of customer churn. By identifying potential churn risks, businesses can implement targeted retention strategies to reduce customer attrition and improve loyalty.  With so many benefits, it is no wonder that businesses use AI-powered CRM for various business use cases. Let’s have a look at some of them:    https://www.youtube.com/watch?v=j8-8i1LNk3k&t=624s Top AI CRM Use Cases By analyzing

Everything You Need to Know About Gross Revenue Retention RevOps 10 min In a world where every organization is looking to acquire new customers, an often overlooked source of revenue is – Revenue Retention. Revenue made by retaining customers is the lifeblood of a successful organization. Retained customers often have higher lifetime value, reflecting their satisfaction and loyalty. Satisfied customers also contribute to a positive brand image and word-of-mouth referrals, giving companies a competitive edge.    Moreover, long-term customer relationships offer opportunities for cross-selling and upselling, while their feedback helps businesses refine and enhance their products and services, ultimately driving sustained growth and success. Revenue retention is pivotal for companies because it signifies the ability to sustain existing customer relationships and, consequently, maintain a stable revenue flow. Retaining customers not only lowers customer acquisition costs but also bolsters long-term profitability and growth.  To measure the revenue for retained customers, companies often use a metric called Gross Revenue Retention (GRR).    What is GRR? Gross Revenue Retention refers to a business’s capacity to keep its current customers. When a business successfully holds onto its customers, it maintains its revenue. In more straightforward terms, Gross Revenue Retention is the percentage of customers a business manages to keep at their current pricing or contract value. It stands as a pivotal customer retention metric for subscription-based companies and those operating in the SaaS industry. The comprehension and monitoring of GRR enable them to assess the overall efficiency of their customer retention tactics. The significance of Gross Revenue Retention goes beyond customer retention; it also functions as a gauge for prospective investors who consider this ratio when assessing a company’s investment suitability. How to Calculate GRR The Gross Revenue Retention rate formula measures the percentage of current customers retained over a specific timeframe. You can determine it using the following GRR formula: In this equation, MRR start represents the Monthly Recurring Revenue at the beginning of the month. This figure represents the recurring revenue at the outset of any period for which we want to compute the Gross Revenue Retention. Churn signifies the decline in revenue resulting from customers canceling their subscription or terminating their contract with the company. It represents a total revenue loss. Contraction, on the other hand, denotes the reduction in revenue caused by customers switching to a less expensive subscription plan. It entails a partial revenue loss since the customer’s revenue has decreased, but the revenue stream is not completely terminated. Let’s consider a quick example to calculate GRR for company XYZ, using the following financial figures: – Monthly Recurring Revenue: $15,000 – New Sales: $2,000 – Upselling to existing customers: $2,000 – Customer Attrition (Churn): $1,000 – Customer Downgrades: $1,000 By using Gross Revenue Retention rate formula: GRR = (15,000 – (1,000 + 1,000)) / 15,000 GRR = (15,000 – 2,000) / 15,000 GRR = 13,000 / 15,000 GRR = 0.8667 (rounded to 2 decimal places) GRR = 86.67% As mentioned earlier, the calculations do not include new sales and upselling. After this calculation, we find that XYZ SaaS company has a GRR of 86.67%, indicating that it successfully retained 86.67% of its revenue from existing customers. Apart from GRR, another popular metric used by organizations to measure revenue retention is NRR.  What is NRR? Net Revenue Retention (NRR) is a customer retention metric that assesses a company’s ability to grow its revenue from existing customers. It considers the revenue generated from current customers while considering any losses due to churn, contraction, or downgrades. NRR provides insight into the overall health of a company’s customer base and its effectiveness in retaining customers and expanding revenue from those customers through upselling or cross-selling. The formula for calculating NRR is as follows: A positive NRR value indicates that a company is retaining its existing customers and increasing revenue from them. Conversely, a negative NRR suggests that losses from customer churn, contraction, and downgrades are outpacing revenue growth from the existing customer base. Gross Revenue Retention vs Net Revenue Retention Gross Revenue Retention (GRR) and Net Revenue Retention (NRR) are two important financial indicators that underscore a company’s capacity to hold onto customers and sustain its revenue. The key difference between GRR vs. NRR centers around whether expansion revenue is considered. GRR concentrates solely on revenue derived from current customers without factoring in any supplementary income stemming from upsells, cross-sells, or upgrades. This metric offers insights into your company’s ability to maintain its fundamental revenue streams over time. The greater the proximity of GRR to 100%, the more favorable the situation. However, this is contingent on the size of the customer base. Small and medium-sized businesses (SMBs) tend to experience higher churn rates and lower retention figures. Conversely, NRR considers retained customer revenue while also incorporating growth-related activities, like opportunities for upselling and cross-selling to existing clients. NRR presents a more holistic view of your company’s overall retention performance. NRR serves as a useful tool for business owners and stakeholders to assess the business’s expansion. It functions as a growth indicator, offering insights into the effectiveness of cross-selling and upselling strategies. An NRR value greater than 100% signifies growth, while NRR at 100% denotes a static business. When NRR is below 100%, it indicates a decline. According to advisor Dave Kellogg, a solid median NRR for private companies stands at 104%. It’s important to emphasize that NRR exclusively considers existing customers. To gain a comprehensive understanding of the business’s performance, it’s advisable to combine NRR with other metrics. Now that we have understood the difference between Gross Revenue Retention vs Net Revenue Retention, let’s understand the importance of tracking GRR for companies.  Importance of GRR As mentioned before, Gross Revenue Retention serves as a stability gauge for SaaS companies, revealing the initial revenue at the start of a period and how much has been eroded by the end. SaaS firms monitor GRR to gauge how strongly customers have either severed ties with or weakened their connections to the company. A higher customer loss may signal potential problems with

Everything You Need to Know About Sales Commission Structures RevOps 10 min Compensation (of which sales commission structure is a critical part) plays a highly influential role in driving rep behavior. And it becomes particularly important when reps don’t want to stay around in one company for too long.  It takes an average of 3 months for a new seller to interact with buyers, 9 for them to perform competently, and 15 for them to become top performers. However, the average tenure that reps remain with an organization for is only 1.4 years in 2022.  This shows that once reps have learned all they can with you, they’ll move on to a new organization (most likely one that pays better).  Just hiring the best reps isn’t enough to increase sales. They should be motivated enough to stick around through the ups and down and simultaneously improve their performance.  To achieve this, you need to tailor a sales commission structure template that gives them the incentive to always come out on top.  Let’s find out how. What Is a Sales Commission Structure? “Sales commission” is the amount sales reps earn on each sale.  “Sales commission structure” outlines how you will compensate the rep with a commission and how much this amount should be, based on the sale.  It also includes the timelines for commission payment, i.e., when you’ll pay reps their commission—weekly, monthly, quarterly, or something else.  Remember, the plan you choose directly impacts your reps’ earnings. Therefore, it’s vital that you set up a fair and sufficiently rewarding sales commission structure template. How Does a Sales Commission Structure Compare to a Sales Compensation Plan? Sometimes, commission may be confused with compensation. Here’s a simple tip to differentiate between them.  A compensation plan includes the rep’s total earnings—salary (or fixed pay), commission, incentives, bonus, and on-target earnings (OTE).  As you can see, the commission is just one part of the overall compensation plan. It doesn’t denote compensation in its entirety. Types of Sales Commission Structure Templates There are several sales commission structures you can choose from. It could also be that your team or organization needs a unique sales commission structure template. So, sometimes you may need to combine a couple of these plans.  Below are 10 popular structures you can try.   1. Straight Commission This sales commission structure doesn’t include a base pay or fixed salary. Instead, reps earn 100% commission based entirely on deals they close.  For instance, if a rep closes a deal for $100,000 and the straight commission rate is 10%, the rep will earn $10,000 as commission (without any base pay).  Straight commission is gradually moving out of favor among sales organizations because retaining talent is challenging without the security of fixed pay. It only increases reps’ stress levels and may push them to partake in bad sales practices.  Also, each rep has their own set of skills and practices that make them unique. A straight sales commission structure template doesn’t account for these skills.  When to use this structure:  Shortcomings of the straight commission structure don’t completely nullify its usefulness. You can turn to this plan if you’re a startup or a small organization with limited capital. 2. Base Salary Plus Commission This structure is the most widely adopted across industries and organizations.  Typically, a rep’s compensation is split between salary and variable pay (which includes commission). The split may be 50/50 or 60/40, depending on what you can offer as a salary while still incentivizing reps.  A “base salary plus commission” structure works well because commission motivates reps to continue improving their performance, whereas salary acts as a safety net to retain them in tough situations.  When to use this structure:  You can deploy this sales commission structure template if you’re striving to maintain a good balance between your sales budget and commission. 3. Revenue Commission  In a “revenue commission” structure, reps earn a flat commission percentage on each deal won. So, if your rep closes a deal for $100,000 and the commission is set at 7%, they earn a commission of $7,000.    However, this structure again doesn’t consider each rep’s distinctive selling capabilities.  When to use this structure:  Revenue commission works well when your team is small, your product offerings aren’t too complex, or you’re selling only one product with fixed pricing. 4. Gross Margin Commission  The gross margin commission structure follows a similar approach to the revenue commission structure.  However, instead of revenue (ARR or contract value), reps earn commission on the gross revenue (or profit on sales). Say your rep sold a contract for $150,000 but incurred a cost of $25,000 for the company. These costs may include travel to meet the client or a discount for the buyer. Under the gross margin commission structure, the rep will earn a commission on $125,000 ($150,000 less $25,000). Gross margin commission motivates reps to close deals at higher margins, ultimately benefiting the organization. When to use this structure:  If you aim to ensure bottom line profitability, this sales commission structure template can help reps win deals without incurring too much expense. This may also speed up the sales cycle. 5. Tiered Commission  In tiered commission, reps earn incremental commission on each deal closed, depending on the tier in which it falls.  The bigger the deal closed, the higher the tier and the higher the commission earned.  For example, for deals under $50,000, reps earn a commission of 5%, but for deals under $100,000, the commission moves up to 7%, and so on.  Tier Deal Size Commission  A Up to $50,000 5% B $50,000 to $100,000 7% C $100,000 to $150,000 10$ Tiered commission encourages reps to continually achieve and exceed targets for higher rewards. But, to maintain your business’s profitability, you may want to cap the maximum commission a rep can take home. When to use this structure:  A tiered commission structure works best when scaling your team, as it promotes over-performance and separates top performers from low. Not just that, it also motivates average and low performers to push

How a Revenue Intelligence System Eliminates CRM Data Challenges RevOps 10 min In this blog

Migrating your CRM to Salesforce? Don’t Leave Behind Crucial Activity Data! RevOps 10 min Salesforce data migration is a challenging project for most operations leaders. Your CRM system contains critical information about your customers that can help drive positive business outcomes. When you decide to migrate to a new CRM system like Salesforce, you don’t want to lose out on this valuable data from the old system.  But loss of critical activity data during Salesforce data migration is common. This loss directly translates to missed opportunities that already exist in your CRM. In this article, we will explore the challenges related to capture of activity data while migrating your CRM to Salesforce. And how you can avoid this major pitfall with the right data strategy.    Activity Data Loss During Salesforce Data Migration The biggest problem during Salesforce data migration is loss of historical data. This does not include data related to opportunities and accounts in the old CRM. This data loss caters to multiple fields within opportunities. Examples include email exchanges, opportunity contacts, or notes associated with deals. With such crucial activity data missing, revenue teams lose sight of many deals. With the loss of this activity data, revenue leaders miss out on finding answers to critical questions that move the revenue needs. Examples include: How many emails were exchanged? What was the context of those emails? Who were the contacts involved in the deal? What was the role these contacts were playing in the purchase process? What were the pricing related details that came up during conversations? These granular details give a clear view of the sales pipeline to revenue leaders. And armour them with information they can use to coach their reps better and lock in more deals every quarter. This data also provides leading indicators that can act as predictive measures of future performance. Despite best efforts, this revenue data gets lost during Salesforce data migration. There are different data transfer woes operations leaders face when they migrate their CRM to Salesforce. Failure to transfer the data under the right fields. For example, instead of going under the “opportunity” field, it might get fed into the “account” field. The ability to parse the metadata from Gmail to get into Salesforce remains a challenge.  Even if the data gets added to Salesforce, the activity data is mostly of the migration date and not the actual date in which the activity actually took place. This makes the information lose its relevance.  There is a chance of losing a lot of other data from the old CRM while migrating to Salesforce. While most CRMs do offer plugins to transfer activity data into Salesforce, these plugins do not work effectively under all conditions. As a result, they end up being unreliable mediums to capture data.  Most tools also require the contacts to be already in Salesforce for the activity to be captured. When nobody adds the contacts, associated activities automatically get missed out from the new CRM.   https://www.youtube.com/watch?v=wpJxlPnfIoQ&t=2727s 5 Alarming Consequences of Data Loss The consequences of activity data loss during a CRM data migration can have catastrophic effects on your business.  Data loss can cause a direct dent on your revenue engine. Let’s look at some of these alarming consequences: 1. Poor deal reviews Deal reviews form an integral part of closing more sales. It helps sales managers know what’s going on in their pipeline, and devise strategies to pivot wherever necessary to avoid risks.  Data is the fuel that runs successful deal reviews. To conduct effective reviews and 1-1 coaching sessions, sales teams need access to the right data. They also need to be able to use that data to drive intelligence across the revenue engine. But with lost data during migration, sales teams lose access to critical revenue data that can help them close more opportunities during the quarter. And with missing data, organizations fail to create those data-driven strategies that can help devise successful sales strategies.  For example, backing up data in deal reviews during CRM data migration becomes questionable. Without historical data and associated activities getting tracked, sales teams won’t know which stakeholders are a part of the buying committee.  In short, without the right data, deal reviews fail to make sales teams more successful. The results in failed campaigns to drive sales forward, more gaps in the selling process, frustrated sales teams and inability to meet quotas. 2. Inaccurate sales forecasting Sales forecast is a critical element of running a successful revenue operations function. With sales forecasting numbers, revenue leaders are in a better position to carefully align resources towards the right areas.  But less than 50% of sales leaders and sellers have high confidence in their forecasting accuracy. Without the right data at the right place, making accurate sales forecasts becomes very challenging. To be able to make an accurate forecast, revenue leaders need access to historical data to get a visibility of how the sales pipeline is progressing at an organizational level. Bit losing this critical data during a migration project translates into lack of clarity into critical questions like: Which are the deals moving towards closure this quarter? What is the stage different deals are at? Which deals are not likely to close? Longer sales cycles, missed quotas and an unclear picture of deals make predicting accurate sales figures an ambiguous exercise. And relying on human tendencies like guesswork and instinct give rise to ambiguous forecast numbers. Complete and trustworthy data in CRM and other GTM tools is the first step to achieving confidence in sales forecasts. Without this unified data visibility, sales teams fail to focus on the right deals and fall prey to risks that fail to predict the fate of their deals.  3. Surge in operational cost  The loss of data during Salesforce data migration is usually realized when the decision to migrate to Salesforce has already been taken. This puts businesses in panic mode as the possibility of significant data loss hits them in the last few days of the migration.  The second realization that hits organizations is

MEDDIC vs Challenger: What’s the Difference? RevOps 10 min Hitting targets is one of the topmost goals for any sales rep. Understandably, all sales teams want to perform consistently well and achieve their goals.  But if you’ve seen your teams struggle in the last few years, you’re certainly not alone.  A recent crowdsourced survey by SaaStr shows that only 18% of sales teams hit a 70%+ quota attainment level. Average quota attainment for reps is down 5 points in 2023 from 2021. Quota attainment is also down for 5 out of 7 such teams.  To change the narrative, you’re probably digging into different sales methods that more successful businesses use. Or, you may simply want to level up your sales game as organizational growth becomes stagnant.  The first few methods popping up will undoubtedly be the MEDDIC and Challenger Sale. Both are useful with proven results for different companies. But confusion may persist on MEDDIC vs Challenger Sale and which one’s the best for you.  We’ve put together a quick overview of both methods that could help you make a decision.  Understanding the MEDDIC Academy Sales Method For 71.4% of sales professionals, only 50% or less of their initial leads are a good fit for their ICP. Reps blame poor qualification of potential customers before taking them through the entire sales process for 67% of lost deals.   There’s one method that shines in these situations.  MEDDIC is a B2B sales qualification methodology used to understand the customer at each stage of the buyer journey. The process drives revenue and business growth by qualifying buyers more accurately.  Here’s how the MEDDIC Academy explains what the process stands for: 1. Metrics What is the quantifiable value of your product for the customer?  2. Economic Buyer Who has the final word on the financial decision at the buyer’s end?  3. Decision Criteria What factors or criteria influence the purchase decision?  4. Decision Process How does the buyer reach a decision?  5. Implicate Pain What is a problem serious enough for the buyer to seek an external solution?  6. Champion Who is the stakeholder most invested in onboarding your solution?  MEDDIC places the focus on customer experience instead of selling with the sole objective of making money. It works because 56% of sales leaders consider engaging and paying attention to gain a client’s trust as the best approach.  With the MEDDIC Academy method, you can: Find leads that are the right fit for you Access critical stakeholders in the buyer committee  Build better forecasts  Boost winning rates  Over time, the MEDDIC Academy has included more steps, such as MEDDPICC, where P stands for paper process and C is competition.  Understanding the Challenger Sale Method Today, 32% of B2B buyers use more sources to research and evaluate processes than before. And 31% spend more time on social media to check out vendors and their solutions.  This means customers enter into a sales transaction with preconceived notions about the product. Reps need to develop an experience going beyond features and benefits. Instead, sellers could challenge the buyer and disrupt their current thinking. This is the Challenger Sale Method. You’re a challenge seller if you: Have a unique perspective of the world Understand the customer’s business in and out Create constructive tension using a casual debate Intentionally dispute the customer’s thinking Push the customer to get out of their comfort zone  Here’s what the Challenger Sale process looks like: 1. Warm-up First up, you build credibility with prospects by researching and investigating their pain points, challenges, and needs. Then, you describe these issues to the buyer in a way they agree.  2. Reframe You reframe the problem as a growth opportunity. This switch is made by sharing an insight that the buyer may not have considered before. 3. Rational drowning You back your reframing with quantitative data and the latest statistics. Numbers illustrate the risk of leaving the problem unresolved. It uses rational thinking to appeal to the customer’s emotions.  4. Value proposition Show the buyer possibilities of a better future. Tie their value drivers with your solution’s capabilities (without explicitly introducing the product).  5. Introducing the solution After the building blocks are in place, you can introduce your product. This is when you explain exactly how it solves the buyer’s problem. With Challenger Sale, you deliver insights into an unknown problem or opportunity in the buyer’s business. Your product is uniquely positioned to solve this problem. By encouraging the buyer to consider new opportunities, a Challenger Seller offers alternative ways forward. But they need three essential skills to succeed:  Teach by providing insights on new or better ways to solve the buyer’s problem  Tailor the message to the buyer’s needs Take control of the sale and guide the customer to closure MEDDIC vs Challenger Sale: How Do They Compare? Some sales experts consider MEDDIC as a sales methodology and Challenger Sale as simply an approach. But there’s more to it.  We’ve listed each MEDDIC vs Challenger Sale comparison below.  Despite the long list of MEDDIC vs Challenger Sale differences, both methods have three things in common: 1. Buyer evolution Both methods take into account the evolving buyer. MEDDIC considers the transformation from the individual buyer to a buying committee with multiple members.  Similarly, Challenger Sale knows that buyers are gathering more information online and contacting the seller later during their journey.  2. Buyer’s drivers Both MEDDIC and Challenger Sale identify the buyer’s value and economic drivers for the selling process.  3. Cross-functional alignment  MEDDIC and Challenger Sale need alignment between revenue teams and leadership buy-in. Marketing managers and leaders provide training and resources for all reps.  Challenger vs MEDDIC Academy Process: What’s the Verdict? Here’s a list of things to keep in mind when considering MEDDIC vs Challenger Sale.   MEDDIC Use the MEDDIC Academy sales process to determine if a prospect is the right fit for your company. It helps teams that are struggling to keep up with the existing sales process and want to improve.  MEDDIC can intervene to help you: Sell to the correct buyer Identify the right stakeholders in a complex enterprise B2B buying committee Regardless of so

Discover Hidden Revenue by Restoring Salesforce Historical Data Missing historical data from Salesforce leads is a big pain. Discover how you can restore your Salesforce historical data with this guide. Salesforce 2023 is transforming how businesses approach ‘growth’. For the last 10-15 years, capital flowed freely. Businesses received funding effortlessly. The only focus was ‘growth at all costs’. Profitability was only considered during the very late stages or when preparing to go public. But today, with capital becoming expensive, there’s a shift in mindset when it comes to ‘growth’. Businesses, big and small, new and old, are being measured on capital efficiency. There’s a tremendous focus on ‘efficient growth’. And how does efficiency work? Efficiency works on the concept of doing more with less.  This is exactly why companies are focusing more on customer success-led growth and account expansions to achieve efficient growth instead of traditional sales and marketing channels. However, there’s yet another channel that is being overlooked – a company’s Salesforce historical data. Unfortunately, most of this data is either missing, incomplete, or outdated. The Problem of Missing Salesforce Historical Data GTM data should be available in your Salesforce CRM. However, a major pain point that businesses often encounter is the incomplete availability of data in Salesforce. While it is crucial for all essential information such as contacts, emails, and meetings to reside in Salesforce CRM, 50-70% of this data is frequently missing.  There are several reasons contributing to this issue.  Firstly, customer-facing teams are typically not incentivized to update the CRM beyond their primary goal of generating leads. Consequently, they may neglect to input crucial details and updates into the system, leading to gaps in the data.  Secondly, although there are existing tools designed to assist businesses and customer-facing teams in capturing activity, they vary in their level of automation. Some tools are fully automated, while others are only semi-automated.  However, since activity capture is not the primary focus or “hero product” of these companies, the functionality of these tools may be limited. As a result, not all data is captured, leading to incomplete information and missing data.  Lastly, as businesses grow and teams expand, the amount of missing data becomes even more significant. For instance, if one person in the team fails to add data to Salesforce, there will be a certain amount of missing data, let’s call it “x”.  However, if the team expands, and there are now five people who neglect to input data, the missing data increases to five times “x”. This accumulation of missing data over time creates substantial Salesforce historical data gaps, which can hinder decision-making processes and prevent businesses from leveraging valuable insights. Restore your Salesforce Historical Data with AI and Automation Given this looming problem of missing data, the real question is – Can Salesforce track historical data?  Absolutely! Nektar can help you restore your Salesforce historical data in the following ways: 1. Salesforce Historical Data Sync Nektar’s Historical Data Capture capabilities provide businesses with exceptional control over their buried historical contacts and activities in Salesforce. From the moment of implementation, users can select their desired time period and effortlessly restore relevant historical data, unlocking a treasure chest of insights. Typically, Nektar helps restore 4-6 times more contacts and 5-10 times more emails and meeting data in the CRM – and this is offered as a ‘welcome gift’ on day 1. The historical data captured by Nektar plays a pivotal role in reviving closed-lost and dropped opportunities. Marketing teams can run more effective account-based campaigns by accessing accounts filled with first-party, pre-engaged contacts. Sellers, especially those who recently joined, benefit from increased context and contacts for every account, even if they weren’t previously managing those accounts. Furthermore, the historical data enables the identification of success patterns and opportunities for process optimization. Nektar empowers businesses to answer critical questions such as the number of contacts required to win a deal, the engagement level of buyers in each deal, essential personas or job titles for winning deals, and the number of meetings it takes to secure a deal. Whatever insights customers require, they can be captured within their data-packed Salesforce, powered by Nektar. Check the gaps in your salesforce reports, with an no-obligation free CRM scan report.   Scan my CRMDownload Sample Report    2. Time Travel Nektar also helps customer-facing teams restore historical data ‘on demand’. We call this ‘Time Travel’. For example, let’s consider Jane, an Account Executive from SellMore, who prospects Molly for Acme and creates an Account in Salesforce. Through Nektar, Molly is automatically added to the account. However, Nektar goes beyond that. It creates four additional contacts associated with Molly, along with emails exchanged in 2021. Among these emails, Jane discovers the name lee@sellmore.com, an ex-SellMore AE whom she doesn’t know. Nonetheless, Jane gains valuable insights about the Acme account by accessing these pre-engaged contacts. This additional context and access to contacts increase Jane’s chances of winning the deal.  Nektar’s AI-driven Time Travel feature identifies contacts and activities related to the Acme account that remained buried in the inbox and calendar of an ex-employee. Nektar’s AI retrieves this data on-demand and seamlessly integrates it into the Acme account. This empowers users with enhanced context and more contacts to effectively manage their accounts.  Notably, Time Travel by Nektar is not restricted to the time period defined for Historical Data Capture. Whether Salesforce Historical Data Capture was configured for 2021 to present or any other range, Time Travel can retrieve data from before 2021, reaching back to the initial implementation of Salesforce in the company if required.  Tap into your Salesforce Historical Data for Efficient Growth Nektar’s Historical Data Capture capabilities offer businesses a powerful solution to address the pain points associated with missing data in CRM systems. With Nektar, companies can regain control of buried historical contacts and activities in Salesforce, unlocking a treasure trove of insights and experiencing ROI from day one. By restoring Salesforce historical data, businesses can revive ghosted or closed-lost deals by accessing pre-engaged, first-party contacts associated with those accounts. Nektar