“The acquisition extends Bigtincan’s lead in AI-driven revenue intelligence by improving B2B sales organization’s ability to scale by delivering insights and recommendations directly to sales reps for better decision-making to increase revenue,” the firm told investors. “The SalesDirector.ai technology links people, activity, and engagement across the buyer’s journey to derive insights, including opportunity risk and relationship strength, and then makes intelligent recommendations. By capturing all sales, marketing, and customer success activity the technology drives actionable revenue insights required to make the right business decisions.”
Bigtincan stated that SalesDirector’s technology would improve its AI-powered insights capabilities and forecasting accuracy.
SalesDirector ingests data from GSuite/Gmail, Slack, Microsoft Office, and Microsoft Exchange and feeds contact data (e.g., Title, Department, Level, Phone) to Salesforce and Microsoft Dynamics. SalesDirector also captures Engagement Signals and writes them back to CRMs as custom fields:
Executive Engaged on Opportunity / Account
Single or Multi-Threaded Opportunity Relationship
Last QBR Complete / Next QBR Scheduled
Partner / Sales Engineer Engaged on Opportunity
Next Step / Meeting Scheduled
AI tools include stakeholder identification, individuals who are supporters or detractors, disengaged stakeholders, account risk scoring, sentiment analysis, and deal health.
“Every organization has to be more productive,” said Bigtincan CEO David Keane. “With the Sales Enablement market shifting towards a more holistic approach encompassing Revenue Enablement, we can deliver more value to our customers by providing full-cycle sellers with AI-driven recommendations on the next best actions based on intelligent sales analytics from SalesDirector.ai.”
SalesDirector pricing begins at $29 per user per month for activity capture. Revenue Insights pricing is not published.
Bigtincan will incorporate SalesDirector’s functionality into its product suite and phase out the SalesDirector brand.
“Traditionally, when we do small tech-focused acquisitions, they become part of the Bigtincan product suite, so that capability gets added to the existing platform we have,” said Keane. “We don’t tend to run these things as separate businesses, mostly because we miss out on some of the benefits for our shareholders of taking it all together and taking that technology and really getting in the platform. This is no different than our existing strategy – embed, connect it all together and make it something that our customers can choose to add. We do believe that it is all about choice, and we want people to be able to buy these technologies from us as additional value-added options. I think that’s going to be the case here as well.”
Bigtincan paid $1.2 million in cash and equity for SalesDirector.
The entire SalesDirector team is joining Bigtincan.
Bigtincan, listed on the Australian Stock Exchange, has acquired a series of RevTech companies, including ClearSlide, Brainshark, and VoiceVibes.
Dale earned a BA and MA from Valparaiso University with a concentration in ethics. He also received an MBA from the Kelley School of Business at Indiana University.
What experience have you had developing AI tools?
As the SVP of Product Management at Salesloft, I am working with our team to bring Rhythm, Salesloft’s AI-powered signal-to-action engine platform, to life. Rhythm ingests every signal from the Salesloft platform as well as signals from partner solutions via APIs, ranks and prioritizes those signals, and then produces a prioritized list of actions. The action list gives sellers a clear, prioritized list of actions that will be the most impactful each day, along with an expected outcome prediction. In addition to simplifying a seller’s day-to-day, it helps them build their skills by providing the context about why each action matters.
AI is becoming increasingly important in RevTech, with many of our interactions being mediated by AI. Where do you see AI having the biggest impact on Sales reps between now and 2025?
AI will enable significant improvements in both seller efficiency and effectiveness. The most obvious impact will continue to be automating away low-value, repetitive work. What will surprise people will be the rapid advance and adoption of AI to suggest next best actions to take and content to use in those interactions with buyers. A typical workday for a seller will see them greeted by a recommended list of actions to take each day. Each action will be prioritized based on where the seller sits in relation to their targets, with each action accompanied by suggested content where appropriate. For instance, I might see a suggestion to respond to an email from a champion in an in-flight deal. The recommendation will include suggested text for the response as well as a resource to attach to the email. That’s a future we are actively investing in at Salesloft, which is at the heart of our soon-to-be-released Rhythm product.
Same question, but looking further out to 2030…
As AI becomes more commonly deployed across the sales profession, buyers will experience a more consistent sales experience in each buyer-seller interaction. As this becomes more common, it’s going to raise the bar on what buyers expect from a sales experience today. That will put more pressure on sales teams to deliver consistently in ways that today may seem unreasonable but will be possible with AI assistance.
One of the key ways to raise the seller performance bar will be high-impact, tailored coaching. Manager time is a constrained resource, and seller coaching augmented by AI provides a path to realizing performance improvement without manager time constraints. We should fully expect AI to help coach sellers to hit their goals based on each seller’s unique profile. We can expect AI to evaluate the seller’s entire game (activities, conversations, and deal management) to identify the highest leverage areas each individual seller should focus on to improve. Some of the coaching will be provided by AI at the point of execution, like on a call or when writing an email, with the rest provided throughout the workday as recommendations.
What are the most significant risks of deploying AI broadly across the Sales Function?
Two areas come to mind. First, AI used without clear boundaries in a sales process can lead to problems. If you employ AI and automation capabilities, it should be to allow the user to be better armed to make a decision, not make it for them. AI tools should not replace the human touch but rather augment it. There’s a lot of pseudo-science tossed up around the topic of AI, but ultimately, humans understand the nuance of relationships better than machines. One of the ways to address that concern is to deliver models that not only provide a recommendation but can provide the insights that led to it; humans will better trust the model when making decisions based on those recommendations as well as know when to ignore the recommendation.
Second, there’s a privacy component as well. Companies may create AI models that share data about a particular buyer with other companies’ sales teams without said buyer’s knowledge. The buyer may know they shared their data with one company but have no idea that multiple other customers at this company are using that same data. Creating models with this type of function puts companies and sales teams in a high-risk zone that can tread on the unethical. It isn’t clear that building models in that way may be considered legal in the future. If you plan to deploy AI in a sales org, it’s important to understand how data is collected and used.
AI Models are only as good as the underlying training data. How concerned are you about biased models recapitulating discrimination? For example, emphasizing sales skills that are gender or racially biased when evaluating sales rep performance?
It is a legitimate concern. AI products are based on probabilities, not certainties. The recommendations you receive or workflow automations that fire happen based on the probability that the given recommendation or action is right. Not the certainty that it is right. In a good product, the model is correct more often than a human would be when faced with the same decisions. At times, this is because the model can evaluate a larger set of factors, and in some cases, it is simply that machines can apply rulesets at a higher level of consistency than humans.
One of the key determinants of the AI model’s value is the dataset upon which it was trained. If the dataset does not properly represent the real world, the model will produce results that are either biased or provide poor recommendations. We’ve already seen several examples of that with image editing software that didn’t include black-skinned people in the training dataset. This led to either poor outcomes or worse dehumanizing results when the AI product was used in the real world. If you plan to deploy AI in your business, you should ask the provider what precautions they take to prevent bias in their models. We are very intentional about removing factors that could lead to bias in our training datasets. Still, it isn’t something I see most technology companies paying attention to in the revenue tech space.
How do you curb racial and gender bias when performing sentiment analysis?
We take great care at Salesloft to remove things that would lead to discriminatory factors. For example, for our Email Sentiment model, one of the ways we prevent bias is by removing all mentions of people’s names within the email because that could provide clues to their gender, race, or ethnicity. We do that kind of preprocessing with any data we use in an AI model before we build our models.
One of our assets is our scale. We’re fortunate that we operate globally and are the only provider in our space with offices in the Americas, Europe, and APAC. As a result, we work with organizations of all sizes globally, including many of the world’s largest companies. That means when we build models, we have one of the largest datasets in the world for sales execution. This enables us to train models based on datasets with both breadth and depth. When we build a model, it is easier to train it in a way that fairly represents reality and includes safeguards to avoid racial or gender bias.
AI will increasingly be deployed for recommending coaching and mediating the coaching. What concerns do you have about replicating bias when coaching?
As with any AI product making a recommendation, the potential to make a recommendation with bias is a concern that needs to be addressed when building models.
We take our responsibility to avoid bias in any product we release very seriously. The revenue technology industry as a whole hasn’t demonstrated a similar commitment to avoid harmful bias as of yet. I don’t hear other companies talking about proactive steps to avoid it, but I think that will change. We’re monitoring potential governmental action in both the US and EU that will require companies to raise their standard in this area. It is only a matter of time before laws are passed that require companies to prevent unlawful bias in their AI products.
Sales activities are becoming increasingly digitized, a boon for revenue intelligence, training, and next best actions. What guardrails do we need to put in place to ensure that employee monitoring does not become overly intrusive and invade privacy?
Let’s start by recognizing it is reasonable for an employer to have insight into what work is getting done and how it’s getting done. On the other hand, getting a minute-by-minute record of how each seller spends their day is unreasonable, as is dictating every action the seller takes from morning until nightfall.
We have to start with the right first principles. I think we can all agree that humans have inherent worth and dignity. They don’t lose that when they go to work. The challenge is that we have some companies in the technology industry that forget that fact when developing solutions. When you forget that fact, I believe that you actually harm the customer that you’re trying to serve. That harm happens in two ways.
First, you lose the opportunity to realize the true potential of AI, which is to serve as a partner that enables humans to do what they do best…which is to engage with and relate to other humans. AI should not be used to make final decisions for humans or to dictate how they spend every minute of their day. Good AI solutions should be thought partners and assistants to humans. It’s Jarvis to Tony Stark’s Iron Man.
The second way overly intrusive technology harms companies that employ it is via employee turnover. It’s no secret that industries that offer low autonomy to employees suffer from high turnover. Most humans fundamentally desire a base level of autonomy; if that’s threatened, they leave whenever a good option opens up.
In short, if the seller is working for the technology instead of the inverse relationship, we’re on the wrong path.
In 2018, Salesforce CEO Marc Benioff argued that the best idea is no longer the most important value in technology. Instead, trust must be the top value at tech companies. How does trust play into ethical applications and AI?
We get to build the future we want to realize. We can either build a future that perpetuates the things we don’t like about today’s world, or we can build a future that elevates human potential. AI can be used to take us in either direction. That means what we choose to build with AI and how we build it should be a very value-driven decision.
We can absolutely build highly effective AI-powered solutions that elevate the people who use them and deliver tremendous business value. The people that believe otherwise simply lack the imagination and skill to do it.
What I love about our team at Salesloft is that we exist to elevate the ability of the people we serve and to enable them to be more honestly respected by the buyers they serve. In sales and life, the way you win matters. It matters to the people you serve on your revenue team, and it matters to your customers.
An emerging category of AI called Generative AI constructs content (e.g., images, presentations, emails, videos). It was just named a disruptive sales technology by Gartner. They stated that “By 2025, 30% of outbound messages from large organizations will be synthetically generated.” What risks do you see from this technology?
There are two immediate risks that come to mind. First, the messages need to be reviewed by a human before they are sent. The technology has made extraordinary leaps forward. I’ve spent a fair amount of time playing around with some of the tools released by OpenAI and others. The output is impressive and also, at times, very wrong. This goes back to the fact that the output is based on a probability that the answer provided is correct. You can get a very professional, persuasive email, or you can get something that approximates a professional email but won’t land well with your intended customer.
Second, it has the potential to make every outbound message sound the same. Generative AI doesn’t replace the need for human skill. It changes the areas of focus for that skill. Specifically, the opportunity for humans is to use Generative AI to help generate a higher volume and variety of ideas and then to edit and refine the output. The returns available to creativity are always high, but they become even higher when everyone is doing the exact same thing in the same way.
Having said that, I see tremendous potential in the technology and think if used properly it will be very valuable to revenue professionals.
Kyle is absolutely right. At the end of the day, a sale happens when a seller connects with a buyer to help them solve a problem. You can’t do that without authentic connection and trust. Generative AI should not replace that human connection, and I don’t think buyers want it to replace human connection. A close friend of mine was a sales leader at a now-public PLG-driven SaaS company. They added sales reluctantly. When they did, the company learned that buyers both bought more from them and were happier customers. That company now wishes it had added sales much earlier. How we interact with one another can evolve as technology evolves, but it doesn’t change the fact that humans are wired to connect with each other. I think emerging tools like Generative AI will help us be more productive, but they won’t replace the need for authentic human connection and trust.
Sales Engagement Platform vendor Outreach will be rolling out AI-Guided Deal Intelligence in 2022. The new Deal Insights functionality provides a consolidated opportunity view that includes a deal overview, deal health, risks, and next best action recommendations from a single pane of glass.
“Deal Intelligence doesn’t just warn you a deal is off track but will actually guide you to help understand what you can do now, in the moment, to change the outcome,” explained Senior Communications Manager Amanda Woolley to GZ Consulting. “Deal Intelligence is going to reach across the Outreach platform and gather signals from all facets of the platform and throughout the customer journey and move from risk identification into action.”
Many of the components of Deal Intelligence such as Sentiment Analysis, Success Plans, Kaia, Commit, and engagement monitoring already exist in the Outreach platform, with the new Deal Intelligence tying together data and insights from the various modules and summarizing them with deal health and next best action recommendations.
“Built on the foundation of our deep machine learning tools like Kaia, Intent, title classification, and more, Deal Intelligence will help remove some of the “best guesses” we revenue leaders have been doing,” explained Outreach CRO Anna Baird. “Deal Intelligence will be gathering signals and let us know – not only when we have a risk – but what we can do to change the outcome! It’s not just a warning light, but a full explanation of how to correct the issue. Deal Intelligence will bring true transparency to opportunity management and help us get to that predictable revenue goal we all want.”
Deal intelligence is gathered across the deal lifecycle and ongoing customer interactions, including sequences, email sentiment, calendaring, Outreach Kaia (conversational intelligence and real-time recommendations), Success Plans (digital salesrooms), and Outreach Commit (pipeline health and forecasting).
“The current ML model looks at the multiple factors and compares them across benchmarks we have collected to derive the [Health Insights] score,” explained Woolley. “Some of the key top-level factors included Decision-maker engagement, activity across email and calls, meeting analysis as well as interaction within Success Plan. For every deal, the ML model determines which factors are positive (‘green flag’) or negative polarity (‘red flag’).”
Both red and green flags are displayed in Deal Intelligence. The Deal Intelligence service summarizes relevant signals, but “given the number of signals captured, it is very hard for a sales rep to drill through every deal.” Outreach’s goal is to “surface all the relevant information for the sales rep in a unified view with the ability to drill deeper as well as take action from within Outreach.”
“Sales reps only succeed when they take the right actions to close deals, yet for far too long they have lacked true visibility into the health of their deals and are forced to turn to intuition and guesswork to select the next best actions to take. Sales leaders and reps have to contend with disparate, dated sales technologies as they strive for an accurate understanding of their deals, pipeline, and forecast. CRM solutions provide a way to store data but rely on extensive tedious manual data entry from sales reps, often resulting in a “garbage-in garbage-out” situation that does not help reps or managers make confident decisions. Point solutions like conversation intelligence offer a way to record conversations and glean insights hours or days later, but at best, they can tell what the reps’ next actions in other systems should be. All are failing to deliver deal observability. And none of them give real-time deal intelligence to sales reps and seamlessly automate the next actions all in one continuous experience. Until now, that is.”
Outreach CMO Melton Littlepage
Part II continues tomorrow with a discussion of Outreach deal health analytics across the deal lifecycle.
There is no lack of companies and their CEOs that go through the motions of woke capitalism, turning it into performative theater to satisfy customers, partners, and investors. Only over time do you see which firms are sincere in their efforts at stakeholder capitalism and which ones view such positions as a way to goose profits and burnish their image.
BP was a perfect example of greenwashing until they befouled the Gulf of Mexico.
I’ve known Kyle Porter, CEO of Sales Engagement Platform SalesLoft, for about nine years. I was impressed when he mothballed his first product because it wasn’t aligned with his belief in sales authenticity. It was a gutsy move. While he didn’t burn his boats (i.e., immediately remove the product from the market), he stopped selling the service and phased out the product while fulfilling current contracts.
Early on he set out five principals for his company. He has discussed them at user conferences and posts them on SalesLoft’s company page:
So when Kyle announced that SalesLoft was internalizing the cost of its carbon footprint by paying for carbon offsets, I asked him about it. He framed the discussion as part of a broader social mission:
“From the beginning, this has been a mission-led business. I didn’t found a company because I wanted to make money in sales, I founded a company because I knew that a business would be the greatest vehicle that I could create to make an impact on the world. And that starts with our customers and changing their lives. It extends to our employees and providing them with a place where they can learn more, grow more, do more, find fulfillment, and serve others. And that extends to our ecosystem and the places that we serve.
If I’ve got influence and capabilities, why not yield those to make the world a better place at the same time…
Einstein said the purpose of life is to serve. I believe that a leader’s role is to serve, and I believe that I’ve been entrusted with a unique story, with capabilities, with resources, with a great business. And it’s my job to be a steward of that and use it to make the world a better place.
So when you look out, you see that we emit 35 billion metric tons of carbon, and SalesLoft is emitting carbon, as well, through our server ecosystem, through our travel, through our office space HVAC. We have an opportunity to take it seriously, and we have an opportunity to have a net-zero impact on the world, then we’re going to take that.
Fortunately, we were able to find a great partner [Green Places] who helps us offset our carbon footprint, and commits us to operating in an energy efficient way.
We stand for something. We act on it. It’s one of the many things that we want to do as a business.”
SalesLoft CEO Kyle Porter (Interview: Michael Levy 8/20/21)
Now, I’m hoping that Green Places keeps Kyle’s feet to the fire on his promise to be carbon neutral. Simply paying for offsets should only be the first step in meeting environmental objectives. The real progress happens when a company works with its employees, vendors, and partners to reduce their carbon emissions. I have no doubt that Kyle is sincere, but even those with the best of intentions need to be advised on next steps and best practices. Just as SalesLoft provides Guided Selling and Next Best Actions to sales professionals, advisory services such as Green Places need to provide Guided Leadership and Next Best Actions to C-level execs.
The SalesTech space is fortunate to have some mensches at the helm (Kyle Porter, Henry Shuck at ZoomInfo, Manny Medina at Outreach, Jeff Weiner at LinkedIn [retired]). Sales has often been a highly competitive, self-serving profession (“coffee is for closers”). Having executives with a stakeholder perspective that preach and implement authenticity, privacy, diversity, collaboration, career development, and environmentalism positions their companies against the stereotypes of the sales profession and helps advance the profession.
Continuing fromPart I, a discussion of Revenue Grid and its approach to Guided Selling.
Revenue Grid looks to take the CRM system of record and supplement it with insights and actions that move deals forward. Insights are both positive and negative. Risk flags include “The decision-maker is not invited to the demo,” “Close data has been changed for the Nth time,” and “Pricing was discussed at the meeting, but no quote has been sent.” By delivering insights to sales reps and their managers, loose ends, which could result in deal losses or delays, are flagged. Sales reps and managers can then act upon these insights. Revenue Grid can also make suggestions based upon internal playbooks and best practices.
In short, AI, historical data, and real-time data are employed to build a set of insights and recommended actions.
Revenue Grid goes beyond engagement metrics at accounts. It delivers a broad set of insights that include competitor mentions, lack of recent decision-makers responses, meetings without agendas, quarterly and monthly trends, and team performance. In January, sentiment analysis will be added to their insights.
An Opportunities view provides real-time pipeline visibility across all accounts. Reps can quickly update any opportunity information with the updates synced with the CRM. Sales reps and managers then have a single-pane of glass displaying current opportunities. Managers are notified of deal size changes, close dates, and scores and can track activity flow.
The Opportunities view includes signals, next steps, last touch, and overview data, providing a quick synopsis of where each deal stands.
Conversational Intelligence records and transcribes voice and video calls, then indexes and analyzes meetings for insights. Corporate email communications are also analyzed for insights. Revenue teams and managers can review call transcripts and listen or view significant moments during the call, with summary topics and insights called out. Conversational Intelligence is also available for coaching and onboarding sales reps.
Conversational Intelligence recordings and transcripts are saved to accounts and opportunities.
A meeting scheduler fronts Conversational Intelligence. Reps can insert multiple time slots with clickable times in their emails or offer a calendaring link. Events are automatically synced between Salesforce and Outlook or Gmail. Other features include calendar delegation (i.e., setting up an admin or CSR to schedule meetings), recurring event scheduling, and group calendaring across the organization.
Salesforce email synching captures emails, scheduled meetings, contacts, tasks, and attachments. Accounts, Contacts, Opportunities, and Custom Objects are available for syncing, and multiple records may be updated. Salesforce admins can set up activity auto-log rules, triggering Salesforce processes.
Sales Coaching offers a team performance view that displays revenue booked by reps alongside leads processed and time spent on external meetings, inbound external meetings, and outbound emails.
A Forecasting report evaluates the target, best case, and committed revenue for the team with plan, commit, and open pipeline values for each rep. Managers can also compare past periods to find trends and set triggers to send notifications when thresholds are exceeded.
An Activity view displays inbound and outbound communications from sales and marketing over time with adjustable time windows. Unfortunately, the activity graph does not rescale, making it difficult to view activity over an extended period.
Revenue Grid also supports Relationship Intelligence, showing an Account relationship map and flagging individuals in the organization with established relationships for introductions or briefings.
Revenue Grid’s sales engagement features include multi-channel sequences, email templates, and email tracking. Channels include email, phone, SMS, and LinkedIn. Sequences may be managed directly from within Salesforce, Outlook, or Gmail. All Revenue Grid capabilities are available in the native Salesforce mobile app, including email analytics, notifications, and sequences.
Admins can perform A/B testing of sequences.
Revenue Grid detects replies from one or multiple recipients, out of office notices, opt-outs, and bounces. It then pauses or halts sequences automatically. It even halts sequences if the recipient is mentioned in an email or meeting invitation.
An email sidebar displays Salesforce data directly within inboxes and suggests relevant, actionable Signals.
“Algorithmic guided selling leverages emerging AI technology and existing sales data to guide sellers through deals, automating manual sales actions while reducing the need for individual seller judgment in the sales process,” wrote Gartner. Guided Selling is data and process-driven, with Next Best Action recommendations that make CRMs actionable.
Guided Selling intelligence is gathered from CRMs, emails, calendars, phone calls, and videos. Engagement is measured across these channels and delivered as a set of insights and revenue signals that support Guided Selling. Signals are Next Best Actions based upon AI recommendations and sales playbooks.
Revenue Grid describes signals as “contextual, actionable notifications that tell your whole sales org what is going well or poorly throughout your whole sales process.” Sales reps can act on recommendations by merely clicking on the signal.
These definitions can all get confusing, but the vision becomes clearer when skipping past the inputs and technology and merely considering which sales and management questions Revenue Grid looks to address. Revenue Grid answers a host of sales rep questions, including
Which deals should I focus on today?
How likely am I to close the deal this month or quarter?
How can I improve my odds of winning this opportunity?
Which deals are at risk and why?
Did I complete all of the post-deal activities discussed on the call?
Have I updated all my opportunities before tomorrow’s deal review?
How can I prepare for a meeting?
Does anybody at my firm have a relationship with key decision-makers?
How is engagement across the account? Am I building relationships with the key stakeholders?
Likewise, managers can answer questions such as
Are sales reps focused on the right things?
Do sales reps know what to do next?
How can I guide reps in each deal?
Which deals are moving, stalled, or at risk?
Do my reps know what to say at meetings? Do our scripts work?
Sales Enablement vendor SalesHood released Coaching Command Center, a set of templates, reports, and prompts to assist front-line managers in elevating the performance and win rates of their teams.
“We’re excited to release more innovation for virtual sales coaching,” said SalesHood CEO Elay Cohen. “We’re committed to helping front-line managers be better at developing their remote teams and boosting their win rates.”
In a call with GZ Consulting, Cohen emphasized that SalesHood focuses on productivity and outcomes for both sales reps and front-line managers, looking to raise the bar for all managers. The new Command Center is a coaching dashboard that analyzes performance and what sales reps are doing. It fosters managerial actions through celebrations, risk identification, and recommending Next Best Actions. A meetings-in-a-box feature supports coaching huddles and hands-on training, with recorded calls as input, and coaching to-dos.
According to Cohen, “curated coaching can be prescriptive” and should be performance and data-driven. It should also be scalable and repeatable, making it easy to schedule classes, coaching, and call reviews. Templates facilitate discussion and coaching. Open questions and training sessions are noted, and sales reps are notified if task assignments have not been addressed before the next one-on-one.
Along with templates, SalesHood provides a library of sales training tools, including battle cards, product playbooks, and win stories. Video recording guidance helps non-training professionals (e.g., product managers, competitive analysts, sales operations) chunk content into modules and cover key topics.
New Command Center tools include programs and coaching activities, team leaderboards, curated team videos, prioritized coaching activities, and coaching templates.
The graphical program tracker displays a data-driven timeline with drill-down tasks, helping front-line managers view programs and coaching activities. The program tracker assists with one-on-one coaching through automated activities, notifications, tips, and scorecards. A notification flag appears in the right corner of the top banner, letting managers immediately access pending coaching activities. For example, if there is a recorded pitch for review, the manager can review the video and offer feedback.
Team Leaderboards summarize team performance across engagement, completion, and performance metrics.
Team videos are submitted and reviewed by managers for comments and celebration. Videos include pitches, demonstrations, presentation dry-runs, deal wins, and stories.
Prioritized coaching activities are delivered to front-line managers on desktop and mobile devices (iOS and Android native apps) with automated coaching activities for pitch practice, role-playing, quizzing, assessments, and story submissions by their team.
SalesHood is packaged with a set of customizable templates for deal reviews, one-on-ones, and even quarterly business reviews. Templates are customizable to reflect the industry, markets, and sales strategies of firms.
“Right out of the box, SalesHood provides solutions for more structured, more efficient, and more lucrative sales team management,” claims the firm.
“Sales coaching creates space for collaborative skill and deal development conversations. Effective sales coaches give sales professionals the responsibility of ownership and accountability for their deal strategies from planning to preparation to close…
No longer will you be in the dark on how your reps are pitching to customers or handling common objections. You’ll be in the know as to how and if they are onboarding effectively. Are they retaining product knowledge? Do they understand the crucial competitive plays? Is their messaging creating interest? Is it aligned with the corporate message?”
“SalesHood Sales Coaching Demonstration” video
Aragon Research predicted that by the end of 2021, 55% of enterprises will have deployed digital sales coaching and learning.
“High-performing sales organizations are now making sales coaching and learning a daily habit,” says CEO of Aragon Research, Jim Lundy. “Top salespeople are constantly practicing, and the best managers conduct regular coaching.” Despite the known correlation between coaching and performance, managers and their teams have been unable to embed this practice into their daily workflows.
Aragon Research placed SalesHood in its Leader quadrant for Sales Coaching and Learning (July 2020), scoring the highest on strategy, but below the other leaders on performance. Aragon listed a broad set of SalesHood strengths, including sales coaching and learning, sales content management, and front-line manager enablement. However, the firm noted that SalesHood lacks market awareness.
Sales Enablement vendor RingDNA released Guided Selling, a set of Next Best Actions (NBA) for sales reps. Guided Selling advises sales reps on what to do, when to do it, whom to contact, and what messaging to employ. Sales managers can create and deploy preferred playbooks to their salesforce, even without face-to-face training. Both inbound and outbound selling plays are supported, helping “implement proven playbooks at scale.”
“When you know what winning deals look and sound like, you know exactly where to focus to improve outcomes,” said RingDNA CEO Howard Brown. “Guided selling uses artificial intelligence to provide revenue teams with tools, insights, and next best actions necessary to win deals, grow accounts, maximize revenue.”
“It’s a fool’s errand to expect a 22-year-old sales development rep (SDR) fresh out of university to develop a consistent, scalable, repeatable prioritization, execution, and qualification process. Be prescriptive in your expectations and methodical in the tools you arm your teams with…for the overwhelming majority of your team—who have never held full-time, quota-carrying roles and aren’t able to think strategically yet—you must be prescriptive. You need to show them how to think strategically and tactically as they approach their daily work.”
TOPO analyst Phoebe Conybeare
Guided Selling is embedded into the Salesforce Sales Cloud and delivers prioritized actions for opportunities, contacts, and leads, helping reduce sales rep planning time. The AI-powered task list recommends the tasks that will put sales reps on “the shortest path to revenue.” The task list is dynamic, updating based upon prospect behavior. Thus, priorities are reassessed based on prospect interaction with e-mails, web forms, multi-media, and social media.
Guided Selling includes a set of best-practices templates based upon billions of sales interactions monitored by RingDNA since its 2012 launch. Salesforce Dashboards help managers optimize cadences and messaging, allowing them to test and refine rep workflows. Cadence activities across e-mail, phone, text, and social are synchronized with Salesforce.
Gartner stated that 51% of sales organizations have deployed or plan to deploy algorithmic-guided selling over the next five years.
“Intended to augment more traditional sales tools, such as sales playbooks, algorithmic-guided selling uses sales data to boost the seller’s ability to engage with prospects…Algorithmic-guided selling leverages artificial intelligence technology and existing sales data to guide sellers through deals, automating manual sales actions while reducing the need for individual seller judgment in the sales process.”
Tad Travis, Gartner VP of Research, “Algorithmic-Guided Selling to Have Significant Impact on Sales Productivity”
“In this new remote paradigm, companies are having to do more with less,” said Brown. “Guided Selling is a total game-changer for sales teams, as it uses AI to focus reps on next best actions while empowering them to build stronger relationships and better solve customer problems.”
ABM Platform vendor 6Sense announced that it is on target for its third consecutive year of at least 100% growth. The firm has also rapidly grown its customer base with a 204% growth in customers since January 2019, and 54% growth since January. Its net customer retention rate is 109%, indicating a strong ability to renew and upsell its platform.
LinkedIn employment figures also indicate strong growth, but at a rate slower than customers and revenue, an indication of increased revenue per employee. LinkedIn employment grew 72% over the past year and 192% over the past two.
“6Sense was founded upon the vision of transforming B2B sales and marketing with a next-generation platform that engages target buyers at exactly the right time,” said 6Sense CTO Viral Bajaria. “Our patented AI-powered capabilities, including 6sense’s time-based predictions and industry-leading account identification capabilities, continue to be differentiators in the market — and deliver real business value to our customers.”
6Sense continues to invest in platform development with the rollout of new ABM capabilities in 2020:
Native Retargeting, which programmatically serves display ads to all website visitors or visitors from target accounts
A LinkedIn advertising integration for account targeting across all ad types
AI-based Next Best Actions, a set of prioritized actions recommendations for BDRs across the buying committee.
Model Metrics, which provide customers with self-service analytics which assess the impact of 6sense’s predictions on pipeline and revenue
CMO Latané Conant cited a series of benefits enjoyed by 6Sense clients, including a 75% higher conversion rate, 40% higher win rates, and a 50% increase in contract values.
Inc. recently named 6Sense the 5th Best Place to Work in the small and medium business category.
“6sense believes that culture is based on trust, open communication, dedicated leadership, and a fun space where employees can take risks. We take everyone’s opinion into account, from the very top to the bottom. Employees take chances, put more responsibility on their shoulders, and work hard for one another. We are a team-first, people-centric organization that prioritizes teamwork above all else. Our weekly all-hands meetings give everyone an opportunity to have their voice heard.”
6Sense Inc. Submission
6Sense closed a $40 million Series C round in January led by growth equity firm Insight Partners, raising its total funding to $105 million.
Content intelligence vendor PathFactory announced a partnership with ABM Orchestration vendor 6Sense to “give marketers complete visibility into the quality of account engagement, as well as what content and topics are accelerating them through their customer journey.”
partnership taps 6Sense’s account identification capabilities and combines it with
PathFactory’s content consumption data, providing richer account engagement
intelligence. “They can even watch a buying committee’s activities
populate and track their journey in near real-time,” said PathFactory.
Account intelligence is synced with the CRM and displayed to sales reps,
helping them understand which content and topics resonated at target accounts.
offers a set of content tracks, either defined by marketing or PathFactory’s
AI. Content tracks are a sequence of relevant content associated with
specific calls to action. Content tracks “keep people engaged longer and
helps them self-educate” while encouraging them to “binge on your content.”
By assessing which individuals and accounts are binging on account tracks,
PathFactory can determine when accounts are “getting serious.” Highly
engaged accounts are more likely to turn into deals.
insights suggest the next best content and next best action, with PathFactory
personalizing content tracks in real-time. PathFactory tracks engagement
at both the individual and account level while assessing content attributes
such as type, topic, and reading length.
“While B2B marketing organizations have invested heavily in ABM over the past several years, many marketers still struggle to successfully execute campaigns, scale programs, and report on results. We are confident this integration will give marketers the unprecedented ability to optimize the customer journey and generate revenue from their ABM efforts.”
Dev Ganesan, CEO of PathFactory
PathFactory clients do not require a
separate 6Sense license.
“PathFactory and 6sense are marrying
two of the most critical data sets necessary for successful ABM execution,”
said Jason Zintak, CEO of 6sense. “With 6sense’s industry-leading account
identification capabilities and PathFactory’s content consumption data, sales
and marketing teams can get deep insight into anonymous buying behavior of
individuals and accounts, and deliver hyper-personalized content journeys.”
PathFactory placed 186th on Deloitte’s Fast 500 list, and Gartner named them a Cool Vendor in their 2019 Technology Marketing category.