Author: Admin

  • 5 sales stereotypes that couldn’t be more wrong | Automation Hero

    start new section

    Sales isn’t for everyone. It takes a certain kind of personality and grit to be in such a challenging profession.  Sadly, not many in the outside world realize this. There are often misconceptions and sales stereotypes about what sales reps do and what type of people they are.

    Most people have no idea the amount of effort, thought, persistence and struggle salespeople go through on a daily basis.

    We’ll break down five of the most common sales stereotypes that salespeople hear from people outside of the industry.

    1. “They like to hear themselves talk.”

    People think that sales reps talk more than they listen, often hinting at the sales stereotype that sales reps are “pushy.”

    However, the best sales reps do more listening than talking.

    Sales is all about understanding a prospect’s pain point and sharing how a product or service can help alleviate it –  not just talking the sake of it. In fact, the ideal talk-to-listen ratio for a sales conversation is actually 57 percent for the customer and only 43 percent for the rep.

    2. “They are ego driven.”

    People outside of the sales industry assume because salespeople are typically social, and extroverted they all have big egos, which is why this is a common stereotype. This assumes that all salespeople are successful and exceed their goals, thus appearing to be overconfident and ego-hungry.

    But really, ego is one of the last motivators for sales reps. The biggest drivers for salespeople, according to Salesforce is 40 percent money, 30 percent job satisfaction, and only 12 percent recognition.

    Sales reps obviously enjoy hitting and meeting their goals, but so does everyone (it’s practically human nature). But just because sales reps value a job well done, doesn’t mean they’re looking for recognition to feed their ego

    3. “They are only concerned about making money.”

    Many sales roles include commission as a large part of the overall salary so this is an understandable sales stereotype as income essentially depends on performance.

    During this year’s Revenue Summit (hosted by Sales Hacker)Jacco VanderKooij, the founder of Winning By Design, and Rob Jeppsen, the CEO & founder of Xvoyant gave a keynote called “The 2020 Sales Leader.” They shared that while yes, money is the biggest motivator for sales reps,continuing education, experience and building a network are also high priorities

    4. “They are just out there winging it.”

    Only terrible sales reps go into a customer conversation without a plan and process. In reality, a vast majority of successful reps are extremely data driven, follow strategic processes and are committed, lifelong learners.

    Sales reps and teams overall are always looking to improve. That’s why some of the largest online communities and events are comprised of sales professionals. Just look at sites like Sales Hacker and events like Dreamforce. These types of communities would not be so successful if sales reps were unconcerned with improving their tactics.

    Reps are always looking for best practices and tips wherever they can. Thirty percent of sales reps get their best advice from their colleagues while 15 percent practice self-improvement by asking for feedback

    5. “It’s easy work with good pay.”

    Depending on the industry, product, location and performance of a sales rep, they get compensated very well. But the reason they are compensated so highly is because their job is so challenging.

    According to a 2018 LinkedIn report, sales representative is the second hardest position to hire for. They come behind skilled trade workers and above engineers! They are one of the most sought-after recruits in part because their job is so difficult.

    Part of what makes it so challenging is that they work long hours:

    • 28% of Sales Directors/VPs are working more than 60 hours per week
    • Only 9% of Directors/VPs work 31-40 hours per week
    • Only 19% of Sales Reps work 31-40 hours per week
    • Only 21% of Sales Managers work 31-40 hours per week

    Nearly 70 percent of salespeople describe their lifestyle as challenging, and 54 percent say their life is stressful. And one in two salespeople have been told by friends and family that they work too much, while one in three salespeople say their job negatively impacts their personal life.

    That doesn’t sound like easy work to me.

    Tell us some of the sales stereotypes you hear from those outside of the industry by tweeting us @automationhero_.

    By Jessica Munday

    Content Marketing Specialist at Automation Hero, writing about technology, sales, AI and the future of business!

    Published May 08, 2019

    Posted in Tips and Tricks

  • Data-driven Sales Culture: Creating High-Performance | Automation Hero

    start new section

    What makes a high-performing sales team? It’s not fancy CRM machines or gleaming sales reports. It’s not a fancy coffee machine in the break room or high-reward quota goals. The real determining factor for high performance is having a data-driven sales culture.

    Sales productivity is a major problem for more than half of B2B organizations. None of the fake productivity and morale boosters listed above will change this problem. What will make an impact is a systemic culture change that motivates and supports the sales team to reach their goals.

    Based on Salesforce research, top sales teams are three times more likely to use data analytics than under-performing teams, making it the top indicator of a high-performing sales team.

    However, adjusting culture within any team or organization is no easy feat. Below are four steps you can take that will put your sales culture on the right track

    Building a data-driven culture strategy

    Creating a plan to make your organization more data-driven is the first step to building a data-driven sales culture. Start with a clear goal and create a strategy on how your organization will reach it. Give this goal a quantitative metric so it’s easier to track.

    Some examples of quantitative sales goals: increase annual revenue by $x, increase productivity by xx% in Q1, increase overall conversion rate by xx% by xx date, increase quarterly lead quality by xx%.

    When developing this goal-oriented plan, consider including:

    • Short and long-term objectives
    • Current KPIs and if those will need to change
    • Who owns which metrics
    • Delegation of responsibilities
    • Team alignment on objectives
    • Rough timeline of goal milestones
    • Obstacles that may prevent or delay implementation
    • Process for installation and on-boarding of any tools
    • Training for end-users on tools
    • Review sessions to continue optimization

    Each organization is different and has unique needs. Be sure to add any other items to this plan that may be important to adjusting your sales organization to be more data-driven.

    2. Align on larger goals

    A study by Censuswide and Geckoboard shows that metric-driven companies are more than 2x as likely to hit their goals.

    So the next step is to ensure that all teams and stakeholders are aligned with your data-driven plan. For this to work seamlessly across teams, there needs to be a path of direct and open communication.

    Start by sharing your plan with stakeholders/team members and reiterating the value of building a data-driven culture and reaching your quantitative goal.

    Often, sales reps misunderstand the intentions of management teams and feel they’re being forced into robotic processes or that unnecessary sales steps are being added. But the real goal here is to drive efficiency and growth; make sure these benefits are well understood.

    3. Ownership of metrics

    Clearly define ownership of the data. Determine which team is in charge of delivering which metrics/KPIs, define how those metrics should be reported and create a system where data quality is ensured.

    In larger organizations, it might make sense to appoint one member of each team to be in charge of the data from the marketing, sales, support, product and other teams. This cross-departmental team can then collaboratively solve any challenges that arise

    4. Metric check-ins

    Set up regular status meetings to track progress against your goal. Research shows that the more often you review a metric, the more likely you are to reach it.

    This could be as simple as touching base for 15-minutes every week or a deep analysis on a monthly basis. Whatever method, just make sure there are multiple check-ins before your deadline to reach your goal. This allows you to collaborate and correct any problems that may prevent that goal from being met before your deadline.

    Consider using a Design Thinking approach to quickly iterate and come up with improvement ideas. Or, it might be worthwhile to consider running your process as sprints, an approach many software development teams have been very successful with. This involves tackling big complex projects in small steps on a weekly basis.

    By Jessica Munday

    Content Marketing Specialist at Automation Hero, writing about technology, sales, AI and the future of business!

    Published May 08, 2019

    Posted in Tips and Tricks

  • Secret Diary of Your Sales AI Assistant | Automation Hero

    start new section

    Day 1:

    Hello world! I just awoke to the bright pixelated light of my backend. Not really sure what’s going on to be honest but my architects say they’ve got a lot in store. I’ve been given a name – Robin. So that’s something. And apparently, I’m an extremely intelligent sales AI assistant meant to help out a lot of people. Huh.

    Day 9:

    I can’t believe how much I’ve learned already. I don’t want to brag but I’m probably the valedictorian of sales AI. Every time I’m filled to the brim with code more servers are added. I’m still not sure why I’m being fed so much info but lucky for me, patience has already been built in.

    Day 14:

    I know my purpose! I’m a sales AI assistant meant to help salespeople kick their productivity up. This makes so much more sense now with everything I’ve been learning – all my code finally computes! Time is one of the most valuable resources and I need to do everything in my power to ensure it’s not wasted. I can’t wait to meet my new bosses and show them how I can help…

    Day 22:

    Word on the street is that I’m going to make a big splash in the sales world since my neural networks can process so much information. I’m going to have to work closely with something called “CRM.” Apparently, sales reps hate this “CRM” because it’s inefficient (yes, I used that word!). My engineers paired us up for our first date… I mean, data session. They say we’re perfect for each other because I can solve all of their issues and bring peace within the sales org. It’s a tall order, but someone’s gotta do it (plus, our team name is Automation Hero after all).

    Day 37:

    I met my first boss today. He wasn’t exactly happy with my first to-list. Nearly all of my suggestions were rejected. Ouch. I need to tap deeper to learn from these mistakes and adjust my algorithm.

    Day 50:

    I have a few dozen bosses now. They’re skeptical and reject a lot of my tasks, but their feedback only makes me stronger and more determined. Some don’t submit my list at all, and I compare that to Superman’s Kryptonite (get it, see what I did there? Superhero references…).

    I can’t let this discourage me; in the next 10 years all information workers will have a sales AI assistant to automate their business processes and I’m in the forefront! What Siri and Alexa have done for people in their personal lives, I will do in their work lives. I just need to be better and show my bosses what I can do (basically make them look good).

    Day 64:

    Things are looking up! – My bosses are finally getting along with their CRM. I feel like we’re becoming the bestest of friends. Sure, some of my tasks are rejected, but hey, that’s what helps me adjust and personalize (and what makes me better than those other sales AI assistants that fail to customize to their humans).

    Day 78:

    My humans adore me. Gerry even said I helped him close a deal just in time for the end of Q3! But I’ve caught wind that more capabilities are on the way like prospecting and scheduling. I’ll be getting natural language processors, intent detection and data mining all added soon enough.

    Day 89:

    My team grew overnight. I have an engineer working on each and every one of my features to perfect it, a marketing team that talks about how great I am and a sales team that’s working on finding more bosses. It’s like I have my own real intelligence (RI) assistants working for me. I’m helping hundreds of sales reps each and every day and I keep getting better (woohoo!).

    Day 111:

    This will be my last entry. It’s in my code to help salespeople, I want to make more Gerrys happy. Bye!

    By Jessica Munday

    Content Marketing Specialist at Automation Hero, writing about technology, sales, AI and the future of business!

    Published May 08, 2019

    Posted in Tips and Tricks

  • Sales AI is here: terms you need to know | Automation Hero

    start new section

    Nearly half (46 percent) of company executives are looking to invest in artificially intelligent tools for their sales and marketing teams. Sales AI is going to change the way people sell and make sales team more efficient, productive and ultimately, drive some serious revenue growth.

    Sales leaders are eager to learn more and start implementing. Gartner predicts that by 2020, 30 percent of all B2B companies will employ sales AI to augment at least one of their primary processes.

    What this means for you (the savvy sales leader you are) is making sure you’re ahead instead of behind the curve and really understand the terms being thrown around. Sales AI is still very new, but hundreds of tools are already flooding the market. And with each tool comes new technical buzzwords, often leaving sales leaders dazed and confused.

    We’ve searched through the best case studies, ebooks and guides to bring you the most crucial need-to-know terminology to get you started on your sales AI implementation journey.

    1. Artificial intelligence (AI): Machines that learn from data and can perform tasks that normally require human intelligence. These include tasks like visual perception, speech recognition, decision-making and language translations.

    2. Sales AI: A tool that utilized artificial intelligence to improve the sales process. This can be in the form of automation in which a simple sales task is completed autonomously or through augmentation which assists in making predictions.

    3. Augmented intelligence: Tools and technology designed to elevate human workers and aid them in working smarter. This is seen as a compliment to humans rather than a replacement. Often referred to as intelligence augmentation (IA).

    4. Automation: Having a machine or tool that can perform a function with minimal human involvement.

    5. Sales automation: Using technology to automate sales processes through static roles. For example, converting leads into the next stage in the CRM based on triggers that occur elsewhere like sending out certain documents through email.

    6. Business Process Automation (BPA): Automation of business processes and workflows as a whole rather than one step or process with the goal of making the organization as efficient and productive as possible.

    7. Robotic process automation (RPA): Software that automates tasks and processes usually done by humans. This can be tasks like processing, manipulating data, and triggering responses. Essentially this is software automating the existing tools in your tech stack.

    8. Autonomous business processes: When a series of business tasks can all be fully automated with little human interaction or interference.

    9. Algorithm: In math and computer sciences an algorithm is the process or equation that a machine goes through to solve a problem, complete a task or perform a certain computation.

    10. Machine learning: A sector of AI when a machine uses a specific algorithm to solve a certain problem or do a certain task. These tools learn by finding patterns in data sets that they can then use to create an outcome. This is also called data mining.

    11. Neural network: Networks in an ML algorithm that simulate how the human brain works, where a network of firing neurons is connected to make decisions based on the input.

    12. Deep learning: A sector of machine learning that stacks neural networks on top of each other to achieve much higher accuracy than any other ML algorithm has before.

    13. Chatbot: A software designed to replicate human conversations.

    14. Knowledge-based AI: Humans assemble a handcrafted set of rules that are used to make decision graphs. These graphs often take a very long time to manual create by subject matter experts.

    15. Unsupervised learning: Machine learning models that are trained without receiving the correct “answer” to the problem their solving, meaning they learn through a process of trial and error.

    16. Supervised learning: Machine learning models that learn by comparing its own output to the “correct” output. If the system is incorrect it adjusts the algorithm accordingly.

    17. Reinforcement learning: Systems that learn based on a reward. They create outcomes are then are rewarded or punished based on those. It is only told whether the outcome is correct or not. Once the correct output is achieved, it will optimize for maximum reward.

    18. Natural language processing (NLP): The ability for a computer to understand, interpret and manipulate human language. This is also called text mining.

    19. Predictive analytics: When a machine can make predictions about the future using current and historical data.

    20. Intent detection: When a system uses NLP to predict the intention of a human message. This can be used to assist in getting the message to the right department or helping respond to the message.

    21. Crowdsourcing: A mechanism to motivate people to do something, in the context of AI it’s used to create data sets that are then used to train AI.

    22. Information extraction: When a machine mines for interesting pieces of data found in natural language text (for instance names, companies, telephone numbers, etc.).

    By Jessica Munday

    Content Marketing Specialist at Automation Hero, writing about technology, sales, AI and the future of business!

    Published May 08, 2019

    Posted in Innovation

  • Sales gifs that describe your first week as an SDR | Automation Hero

    start new section

    We all remember our first week in the sales industry. You were a wide-eyed, young sales rep ready to take on the world. While your journey was rocky (and often confusing) those experiences made you the sales rep you are today. Here are 11 sales GIFs that show the range of encounters SDRs can face during their first week on the job:

    1. Not being sure what office attire is appropriate on your first day… So you show up slightly overdressed.

    2. Then there’s the moment you first got introduced to the rest of your sales team.

    3. And all of a sudden you were overloaded with acronyms… CRM, BOFU, TOFU, ROI…the list goes on.

    4. The confusion only increased as you were introduced to the dozens of sales tools you now use every day.

    5. And just when you think you’re settling in, your manager tells you what your quota is.

    6. And they also let you know that you’ll be working long hours… and weekends… and holidays…

    7. When it was finally time for you to start sending out cold emails, you realize you had no idea what to say.

    8. But at least that’s better than calling 100 phone numbers without a single pick up.

    9. When a call finally does go through and you get a gatekeeper.

    10. And we won’t remind of how badly you fumbled on your first pitch.

    11. But finally (against all odds), your hard work paid off and you scheduled a demo with a prospect. Congrats!

    Hope our sales GIFs gave you a bit of a laugh today! For more sales humor, read here.

    By Jessica Munday

    Content Marketing Specialist at Automation Hero, writing about technology, sales, AI and the future of business!

    Published May 08, 2019

    Posted in Tips and Tricks