“It seems probable that once the machine thinking method had started, it would not take long to outstrip our feeble powers… They would be able to converse with each other to sharpen their wits. At some stage therefore, we should have to expect the machines to take control.” ― Alan Turning To create a predictable outbound sales pipeline, you need to establish a sales goal you are trying to target. For example, if your goal is to sell $250,000 a month through your outbound channel alone and your average selling price is $10,000, you will need to make 25 sales that month. Twenty-five sales may seem like a small number to reach, but if we forecast the pipeline required to achieve this goal, we will find that the number of prospects needed can be significant and require an organized and optimized sales machine for you to reach your goal. Forecasting Your Pipeline To forecast the pipeline required to achieve your goal of 25 sales, I will be using average industry numbers, but you should use your own. Here is my initial logic on forecasting the pipeline required to achieve the goal of 25 sales: · 192 Qualified Opportunities Required: On average, the opportunity to win rate is between 10% and 20%, so let's say to close 25 deals, you will need to get 192 qualified opportunities that your sales team will have to close. We are using a 13% win rate for our calculation. · 1,282 Leads Required: To get those 192 opportunities, you will need to get 1,282 leads based on a 15% lead to opportunity rate. The average lead to opportunity rate is between 10% and 20%. · 12,821 Prospects Required: To get 1,282 leads, you will need to acquire 12,821 prospects if we assume we can convert 10% to leads. The industry average is 5% to 10%) · 64,103 Emails Required: On average, it takes seven interactions before a prospect purchases from your brand. So if we schedule an initial email sequence of 5 emails sent to each prospect, we will have room for some direct follow-up outside the sequence for additional inquiry. With five emails sent per prospect, we will need to send 64,103 emails to get to our goal. Sending Personalized Emails from Salespeople Is More Effective Marketing can choose to send emails from a central company account. Still, it has been proven that emails coming directly from a salesperson will have a much higher success rate in being delivered and being accepted. Here are some industry stats regarding how emails sent by sales reps and are personalized achieve better results than sending company emails: · 99% of companies see better engagement when sending personalized emails. · 98% of companies experience better buyer relationships when sending personalized emails. · Personalized emails have a 29% greater open rate. · Sending personalized emails drive 6x more transactions and have an 8x higher ROI than branded emails. Additionally, by sending emails using one company email account, you will have a more formidable challenge sending cold emails to many prospects. For our forecast, we will assume salespeople will be sending the 51,282 emails since they will get a much higher conversion rate. The only challenge with using salespeople is that we have discovered that the most number of emails a sales rep can send per day is around 50 emails. On average, sales reps send 38 emails per day. Email spam algorithms start sending emails to spam if any one individual starts sending more than 50, without a solid record of consistent email sends and interactions at a higher number each day. Consequently, we will assume that sales can reach out to 200 prospects each month and send out 1,000 emails. Required Sales Team Size Required to Achieve Your Goal With each salesperson sending 1,000 emails per month to 200 prospects, your company will require 64 SDRs and four sales reps. Your team will be sending 64,103 emails to 12,821 prospects and qualifying your prospects to get to 1,282 leads. Then with four sales reps who, on average, can reach out to 320 leads per month, you will be well-staffed to execute on your sales goal. Remember, your SDR team of 64 SDR will need to utilize their email boxes at maximum send amounts to achieve your desired leads; if you want them to send more emails, you may want to increase your SDR team to give their inbox more capacity. To hire such a team, just for the SDRs, it would cost you between $609,224 - $822,557 per month. This solution would give you a negative ROI between -59.96% or -69.61%, and your cost per lead would be a high $475.19 - $641.59 depending on how much you spend on your salespeople. The cost to achieve your monthly goal with an outbound sales team would not be worth it. If you go with a sales robot approach, you would be paying $79.99 per sales robot per month, and the total cost would be $43,676 for 64 sales robots. That would give you an ROI of 472.38% and an average cost per lead of $34.1, one of the low side of costs per lead compared to other marketing channels. With your given price point, a human sales team will not generate a positive ROI for you to hit your goal. You will most likely hit your sales goal but at a high cost. On the other hand, if you use sales robots, you will benefit, but you will have a positive ROI and a very competitive cost per lead. Establishing A Sales Team and Getting A Predictable Sales Pipeline By setting up a team of 64 sales robots and four dedicated salespeople who are sending 64,103 emails to 12,821 prospects each month and following up with leads and closing, you can get to a predictable sales pipeline that has a positive ROI and a low cost per lead. As you run these sales play a few times, you will get more predictable numbers, and you will know when it is time to scale your robots and salespeople. Sales robots have significantly made it cheaper for you to scale your outbound efforts. Also, robots allow you to stimulate additional demand for your offering before bringing on another salesperson. If your sales team time is utilized across multiple channels, you can adjust the model to decrease the number of prospects you are targeting or increase additional sales reps. Notes Mike, A Typical Day For an SDR vs. AE at a Startup, June 12, 2017, Sales Bootcamp https://salesbootcamp.com/2017/06/12/typical-day-sdr-vs-ae-startup/ Sun Wu, AI-Powered Sales Outreach, May 15, 2020, Strategy for Executives LLC DBA Innovatar LeadGen (May 15, 2020 https://www.amazon.com/AI-Powered-Sales-Outreach-Intelligence-Exponential-ebook/dp/B088PXCB8T Shawn Elledge, Average Cost Per Lead by Industry and Marketing Channel: Are You Overpaying? June 27, 2018, Integrated Marketing Association https://www.integratedmarketingassociation.org/blog/average-cost-per-lead-by-industry-and-marketing-channel-are-you-overpaying/

“The playing field is poised to become a lot more competitive, and businesses that don’t deploy AI and data to help them innovate in everything they do will be at a disadvantage.” — Paul Daugherty, Chief Technology and Innovation Officer, Accenture One outbound playbook that high growth companies have deployed over the years to dominate a market is still the leading sales execution strategy for B2B companies. This strategy consists of building an outbound sales machine that has salespeople specializing in two main areas: Sales Development Representative (SDR)- These salespeople focus on getting top of the funnel leads. They go through a lot of prospects to qualify those interested. Their job is to generate lots of meetings and screen prospects to find the leads for account executives. In a given month, an SDR will send out around 1,000 emails (50 per day), and out of those, they may get between 50-100 screening calls and turn those calls into 5-10 qualified leads. Account Executive (AE)- Account executives are focused on quality interactions with each lead they receive. Once they receive a lead, the AE will have another meeting to present the product and then will follow-up with the lead to close the deal. A longer sales cycle will take more time and more meetings for the AE. Leads who are qualified by the AE are called opportunities, and when converted, they will be considered wins. Typically after receiving 5-10 qualified leads from an SDR, an AE may close one or two of those deals. Outreach Playbook Usually, companies have between two to three SDRs for each account executive, but more are always needed. These SDRs should keep AE's busy closing deals. The average Account executive can work with about 80 leads a week or 320 a month. At first, growing a sales team can be expensive, and companies are hesitant to invest. Still, when they forecast their pipeline and realize how many prospects they need to reach to attain their goal, companies have no other alternative but to grow their sales team. For example, a company that wants to reach $250,000 a month through outbound sales and has an average selling price of $10,000 will need to target 12,821 prospects, qualify 1,282 leads, and create 192 opportunities to win 25 deals. The consequences of not growing your team while the market is prime can be significantly detrimental since the sales window where your product will be in demand and have less competition is closing quickly. So those companies who build their sales machine and gain market share are most likely to capture market share and dominate their market. Looking at Sales as An Investment Splitting a salesperson's roles between an SDR and AE also helps with specialization, giving a growth path for a salesperson, and lowering the total investment of hiring a sales team. The fully burdened compensation difference between an AE and SDR is estimated to be between $70k and $100k. · SDR Costs $107k - $147k- Base SDR salary is between $40k-60k with a variable bonus of $20k to $40k and average overhead costs of $47k per year. · AE Costs = $177k - $247k- Base AE salary is between $60k-$100k per year with a variable bonus of $70k to $100k and average overhead costs of $47k per year. For an executive, looking at sales should not be seeing sales as a cost center but an investment. You are making money for each salesperson you hire, and if you are pricing your product correctly and the demand is present, you will always be making money with each salesperson you hire. An Industry Standard A brief search between Indeed and LinkedIn shows that between 23,222 - 53,604 job postings seek a Sales Development Rep and between 35,301 - 39,175 job postings for an account executive. Companies from all industries deploy this outreach playbook with higher average contract values (ACV) highly dependent on this sales playbook. · 89% of companies with over $100k ACV use SDRs · 69% of companies with $25k - $100k ACV use SDRs · 66% of companies with $5k - $25k ACV use SDRs · 48% of companies with less than $6k use SDRs Sales Robots Significantly Improving Existing Sales Playbooks Sales robots are an artificially intelligent machine that resembles a human and replicates particular human interaction and functions automatically. The Sales Innovator robots replicate functions SDR would perform and automates the SDR process. Sales robots look and feel human, and they are used to send out emails just like a human being and interact with prospects to find qualified leads. A sales or marketing person only needs to upload a list of prospects for each robot and create an email sequence and landing page template that robots can use. The robots will automatically send emails, personalized emails, and landing pages and engage with prospects. Based on a prospect's engagement and interest, the robots will then rank each prospect and pass those interested prospects to sales. Sales robots will interact with each prospect through content-rich personalized pages. Robots will know what contents prospects view and interact with prospects through a call to action and prompts offering assistance. Once a prospect wants to interact, a robot will qualify the lead and contact a salesperson to do human interaction. Sales robots can help companies quickly scale at a fraction of the cost while giving account executives an infinite number of SDRs to accelerate their pipeline. Robots free up existing SDR time to focus on closing more deals and allowing them to become more like account executives. Example of Sales Robots in Action At Sales Innovator, we have 65 sales robots actively selling for one salesperson. These robots are sending 148,200 emails to 29,640 prospects each month. Our sales robots are self-service, so our sales cycle does not require a lot of human touches. If we had to hire SDRs to perform this job function, we would be spending close to $7 million, but with sales robots, we can have an army of sales robots for a fraction of one SDR cost. The cost savings are incredible, and our team can reach more people than we could have ever done with real salespeople. Sales Robots Helping You Dominate Your Market If you are a start-up or large company, hiring an SDR team and account executive team to create an outbound sales engine is the way to go if you want to scale your business. With modern technology, you can significantly lower your costs by introducing sales robots to further your growth and reduce costs. If you are skeptical of using robots to sell, you can start with a test and scale based on your success. In the long run, for you to continue to scale and be competitive, sales robots could be a commodity, so invest and make sure you keep your leadership position. Sales robots will be key to helping you accelerate sales and dominate your market. Notes Sun Wu, AI-Powered Sales Outreach, May 15, 2020, Strategy for Executives LLC DBA Innovatar LeadGen (May 15, 2020 https://www.amazon.com/AI-Powered-Sales-Outreach-Intelligence-Exponential-ebook/dp/B088PXCB8T Shawn Elledge, Average Cost Per Lead by Industry and Marketing Channel: Are You Overpaying? June 27, 2018, Integrated Marketing Association https://www.integratedmarketingassociation.org/blog/average-cost-per-lead-by-industry-and-marketing-channel-are-you-overpaying/

“In our business, we talk about emerging technologies and how they impact society. We’ve never seen a technology move as fast as AI has to impact society and technology. This is by far the fastest moving technology that we’ve ever tracked in terms of its impact and we’re just getting started.” — Paul Daugherty, Chief Technology and Innovation Officer, Accenture Artificial intelligence (AI) has become a hot topic in sales and marketing over the last few years, with AI quickly becoming a leading priority for sales teams. Currently, 21% of sales leaders and marketers rely on AI-based applications to improve their sales processes. Companies that have adopted AI claim to increase sales (52%), increase customer retention (51%), succeed at new product launches (49%), and believe they will attain a competitive advantage (85%). Sales leaders predict their use of AI will increase by 155% in the next two years. Analysts believe that the AI market focused on marketing, sales, and customer engagement is expected to grow eightfold, from an estimated present $35 billion to close to $120 billion in 2025. The question should be not whether your company will invest in artificial intelligence, but when will it. In this chapter, we will discuss: 1. What is Artificial Intelligence? 2. How Are Companies Deploying Artificial Intelligence Successfully? 3. How Are Companies Using Artificial Intelligence in Sales? 4. How Will Artificial Intelligence Be Transforming Sales in The Next Few Years? 5. The Rise of the Sales Robot What Is Artificial Intelligence? Demis Hassabis, CEO of DeepMind, an AI company that Google bought, defines artificial intelligence as "the science of making machines smart." Scientists are trying to make machines as smart as humans. We are teaching them to see, hear, speak, and move like humans. Respectively to sales, we teach machines to outreach, engage, qualify, and close as our best salesperson would do. The fact is that we are still far away from having machines taking over a salesperson's job, but each day machines learn new skills that automate sales tasks and enhance the sales process. Machines learn from identifying patterns in a large dataset to make predictions. These predictions get validated with more and more data and become very accurate over time. As companies start to deploy artificial intelligence within their sales process, they will see a gradual improvement in sales outcomes as the machine learns what is working and what is not. For example, a sales AI tool can evaluate all the emails your salespeople send for cold emails. Based on the email's success, the machine can tell you what emails are most successful in what sequence to what target audience. Over time the machine can create email sequences targeting segments in your database. This use case can be valuable for sales teams focusing on sales outreach, and when incorporated with other use cases, the productivity of the sales team dramatically increases. According to a study published by Accenture and the Frontier Economics on the impact of AI on labor productivity, the impact artificial intelligence will have on sales, and the labor force, in general, will be significant by 2035. Countries like Sweden (37%), Finland (36%), U.S. (35%), Japan (34%), and Australia (30%) will have a 30% or greater increase in productivity due to artificial intelligence. This rise in productivity equates to adding an extra $4.9 trillion per year to the global economy - equivalent to an economy greater than Germany's projected size. You can bet by 2035, artificial intelligence will significantly improve our processes. Machine and humans will be working together to build the salesforce of the future. How Are Companies Deploying Artificial Intelligence Successfully? Companies are experimenting with artificial intelligence across all sales processes. There are hundreds of companies applying machine learning in sales and marketing. Early adopters of AI have been big businesses that are digitally mature and adopted multiple AI technologies to help grow and save money. These technologies had C-level support and invested in building AI across various systems. After analyzing hundreds of AI companies, we see AI being used by sales and marketing in the following three main areas: 1. Data Management- These tools manage the integration and machine learning across large data sets to create prediction models to optimize the sales and marketing process. Some examples of tools in this category include data capture, voice recognition, social listening, data management, ML, framework tools libraries, transparency, and compliance. Data management tools have primarily been deployed by large enterprises that generate a lot of data for data scientists to create predictive models. 2. Process Efficiency and Automation- These tools are for sales, marketing, and customer care professionals to optimize and automate their current processes. This category of tools includes sales automation, decision support, lead scoring, price optimization, content development, management, scheduling, decision support, and automation of Martech stacks tools. We also can describe this category as tools to make humans more effective. These tools predominantly stand-alone and fulfill a specific problem using technology and artificial intelligence. 3. Experience Optimization and Personalization -This category goes above and beyond, making humans more effective. These tools leverage the data sets data management tools combined such as customer databases, DMP's, or Google analytics to create omnichannel personalized customer experiences. This category of tools includes personalization, programmatic advertising, auto-generated advertising, customer interaction, advertising personalization, advertising DMP, Chatbots, and digital agents. Sales and marketing teams now trust these systems to automatically make decisions such as ad buying, website personalization, and content recommendations. Due to the need for large datasets required for machines to learn, large organizations have preliminary benefited from artificial intelligent technology. In the chart below created by the Avaus team, we see a lot of disparate technologies providing various AI solutions for sales and marketing. See Avaus's website for more landscape details. Click here to learn more. For organization just beginning to deploy Artificial Intelligence, it becomes essential for these companies to: 1) Identify what they are trying to achieve- There are many solutions available, and companies need to understand what problem they are trying to solve first to make sure they are successful. Some examples of issues to solve include: · Website traffic is down. · Leads are flat · Sales have dropped since last quarter. · Email open and click rates are low. · Advertising is not working. 2) How to pilot AI cost-effectively- Solving a company's identified problem may require one or several tools, and the cost of implementation may be more than the return on investment. So careful analysis and a pilot will help justify a longer-term investment. · Understand how the solution provider will use AI to solve the problem. · Confirm it is solving the identified use case · Find and question vendors to make sure your company knows what will be delivered. 3) Understand the data requirements for each solution -AI needs a lot of data to function. If a company does not have the data, the predictions will not be accurate and will not generate results. Companies need to make sure they have the data requirements for the product to be effective. Companies need to understand the timelines required to get the data; getting the data will slow down a solution's time to market. By understanding the identified problem, the solution, cost, and data requirements, the AI project will have a greater chance of success. How Are Companies Using Artificial Intelligence in Sales? Sales and marketing teams have identified several AI projects that have proven successful across various companies and industries. Here are some of the use cases that companies may want to try. Price Optimization- Artificial Intelligence is helping companies decide how much discount is required to win a deal. Machines analyze the size of the deal in terms of dollar amount, product specifications, number of competitors, company size, territory/region, client's industry, client's annual revenues, type of company: public or private company, level of decision-makers (influencers) involved, timing (e.g., Q2 vs. Q4), a new or existing client, etc. to help predict the right discount. Using AI for price optimization can help companies make sure they win the deal and optimize profits. Forecasting- Sales executives use AI to predict where their teams' sales numbers will end each quarter. Machines analyze past performance, forecasts, existing sales interaction, market conditions, expected renewals, projections, etc., to help forecast sales numbers. A correct prediction allows a company to manage its operation by better managing inventory, costs, resources, and investors. Upselling and Cross-Selling- Artificial Intelligence can help you grow your timeline revenue quickly and economically by helping you sell more to your existing customers. Machines can analyze prior purchase combinations, a client's purchase history and identify which client is most likely to upgrade or buy an additional offering. Using the analysis provided by AI, salespeople will focus on the most likely to purchase clients and create custom sales pitches for each client, saving salespeople a lot of time, minimizing costs, and improving conversions. The net effect is an increase in revenue and a drop in marketing costs. Lead Scoring- When companies have a rich pipeline of interested prospects, a salesperson has to decide what prospect to focus their time on when it comes to closing a deal to hit their monthly goals. Often their decision is based on gut instincts and incomplete information. Machines can look at a prospect's current engagement (e.g., emails sent, voicemails left, text messages sent, etc.), company history, social media activity, and rank which prospects are most interested and likely to close. By prioritizing opportunities, salespeople can focus their attention on the most interested leads and accelerate their sales and lower their time to close a deal. Managing Performance- Artificial Intelligence can help Sales Directors know where to focus their efforts to help their team achieve their sales numbers. A machine can collect salespeople performance numbers on calls, emails, text messages, appointments, leads, etc., and forecast which salespeople are not likely to hit their quota and what prospects are in the greatest danger of not closing. With this information, sales executives can know where to prioritize their time and how to help salespeople achieve their quota, and understand what accounts need their attention. Building Pipeline- For companies building their sales pipeline, AI can help these companies identify companies and prospects who may be most interested in the companies product or service. Machines can analyze what technology a company uses, what products they purchased, their social media presence, financial information, and contacts to propose what accounts and prospects you should be targeting. AI can help salespeople prioritize their outreach efforts and be more effective at closing new opportunities. Close More Leads- Artificial Intelligence can help sales teams accelerate their pipeline by helping sales teams find and qualify prospects that the sales team may not have time to do themselves. Machines can engage via chat with site visitors or reach out via text, email, and phone calls to identify those interested. AI can then pass on the qualified leads to sales based on the prospect's interest level. Salespeople can then focus on closing, and machines can help do the finding. Intelligence Automation and Augment Tasks- Salespeople have been using AI to help them with daily repetitive and tedious sales tasks. Machines can help capture data, take notes, set reminders, create playbooks, and analyze call data to provide feedback. These small tasks take time, and automating them frees sales time to focus on closing more sales. More use cases are being tested and developed by sales teams as we speak. The field of artificial intelligence is still new, and there are a lot more opportunities for improvement. How Will Artificial Intelligence Be Transforming Sales in The Next Few Years? For enterprise companies, artificial intelligence will incorporate into all the technology salespeople use over the next few years. Machines will become smarter as sales teams produce more data that AI can use to perfect their predictions and interactions. In the enterprise, technologies will consolidate into platforms that effectively perform automation and augment the sales process. Platforms like Salesforce, Microsoft CRM, Zoho, Marketo, etc... are already making artificial intelligence a key part of their offering. New point product AI vendors solving use cases will also continue to emerge with deeper integrations into core sales platforms. Platform marketplaces and service companies will continue to thrive as companies enhance core platforms until platforms commoditize their added value. Enterprises have many systems that need to work together, so one system to rule all systems will not be realistic for large organizations. An integrated set of best breed, home-grown, and open source systems will be the norm. Additionally, we see sales robots playing a significant role in the future of sales and AI. As platforms consolidate, we have started to see sales agents, bots, sales robots emerge as a salesperson of the future that can do many tasks that a salesperson performs today and quickly learn from each interaction. Enterprises will start to adopt sales robots that will augment salespeople and give salespeople the time to focus on high-value sales activities. In the future, we can see the birth of many types of sales robots. One may focus on sales outreach, another sales operations, and another on reporting. Humans and machines will work together as a perfect team driving sales for the enterprise. For the SMB market, more turnkey AI solutions will be developed that can help SMB companies adopt AI solutions at lower costs but with more immediate returns. It is challenging for SMB companies to justify having to buy various vendors or an expensive implementation to get AI value. Either AI will become part of their tools, or the solution will have to stand alone and help businesses replace the need for incremental resource costs. Data providers will continue to emerge to help SMB get more value using AI without having a lot of data to start. We see sales robots playing a significant role in sales for the SMB market. Where large enterprises could once dominate the market with their expansive sales force, we see SMB companies equally scale a team of sales robots to dominate markets at a lower cost. Sales robots will open up the playing field for companies to grow and expand since sales robots can deliver more results at a fraction of a salesperson's cost. The Rise of the Sales Robot With the rise of AI and machine learning, multiple companies have been automating and enhancing various sales processes. The combination of AI, multiple technologies, and additional enhancements have allowed companies to build more advanced machines that do not only score and predict but engage and act like humans. These advanced machines are called sales robots, bots, digital assistants, and they resemble salespeople and replicate a salesperson's human movements, interactions, and functions. They can also look human to better assimilate into the selling environment. These intelligent machines, sales robots, can be used for sales outreach and look like real people, send emails, make phone calls, send text messages, and engage like real people. They also can qualify prospects and respond to inquiries. At Sales Innovator, we believe sales robots will be transform sales teams in the enterprise and SBM market. Instead of hiring more sales resources to scale their business, Companies will find it more cost-effective to scale a team of sales robots who can work with salespeople and help salespeople focus on closing. Sending emails, text, and making phone calls will be accomplished by robots and will equalize the playing field when using salespeople to dominate markets. The overall cost to scale a business will be significantly less expensive, and the benefits will be passed on to the customer. The lower cost structure to operate a business will disrupt existing companies that do not adopt sales robots. A recent study published by Oxford economics forecasts that robots could take over 20 million manufacturing jobs worldwide by 2030. In China alone, there could be 14 million robots employed. In the workspace alone, the number of robots in use worldwide increased threefold over the past decades to 2.25 million. Forrester research forecasted that over one million B2B sales jobs already have been lost due to artificial intelligence technologies replacing salespeople. Instead of implementing and integrating various technologies to get AI benefits, companies will buy sales robots that come with all the technology already combined. Sales robots will generate more data through sales outreach efforts that will make AI more powerful, and the robot will become more effective. Over time the robot will be able to take on more human interaction. In the following articles, we will describe the benefits of sales robots and what they do, and why they are worth the investment. AI has given birth to the sales robot to help companies reach more prospects and dominate markets. Notes Tuukka Valkeasuo, Tom Nickels, Ola Ottosson, Katariina Lahdenpää, The AI marketing Landscape is growing at the speed of light, 2019, Avaus https://www.avaus.com/news/the-ai-marketing-landscape-is-growing-at-the-speed-of-light/ Mike Kaput, AI for Sales: What You Need to Know, Feb 6, 2020, Marketing Artificial Intelligence Institute https://www.marketingaiinstitute.com/blog/ai-for-sales Mark Clark, Artificial Intelligence Landscape: Ready To Place Your Bets? March 22, 2017, Digital Engagement Blog https://info.contactsolutions.com/digital-engagement-blog/artificial-intelligence-landscape Here is the Essential Landscape for Enterprise AI Companies, July 10, 2018, AI Trends https://www.aitrends.com/business/here-is-the-essential-landscape-for-enterprise-ai-companies/ Jim Yu, Beyond the AI Hype: AI is here and now, and adoption is rising., February 25, 2018, Online Sales Guide Tips https://www.onlinesalesguidetip.com/beyond-the-ai-hype-ai-is-here-and-now-and-adoption-is-rising/ Victor Antonio, How AI Is Changing Sales, July 30, 2018, Harvard Business Review https://hbr.org/2018/07/how-ai-is-changing-sales Luis Columbus, 10 Charts That Will Change Your Perspective of AI In Marketing, July 7, 2019, Forbes https://www.forbes.com/sites/louiscolumbus/2019/07/07/10-charts-that-will-change-your-perspective-of-ai-in-marketing/?sh=6774d28a2d03 Mike Kaput, 3 Things You Need to Ask About AI If You’re an SMB, May 12, 2020, Marketing Artificial Intelligence Institute https://www.marketingaiinstitute.com/blog/ai-for-smbs Rory Cellan-Jones, Robots’ to replace up to 20 million jobs’ by 2030, June 26, 2019, BBC News https://www.bbc.com/news/business-48760799 One Million B2B Sales Jobs Eliminated By 2020, April 13, 2015, Forrester https://go.forrester.com/press-newsroom/one-million-b2b-sales-jobs-eliminated-by-2020/

Account Based Marketing is a form of marketing that prioritizes marketing and sales focus on the account and their direct needs. Sales approaches are highly personalized and targeted to win over the account. ABM helps you create a really strategic, orchestrated set of activities that allows you to rise above the noise and get people to want to do business with you Instead of relying on a blanket campaign promoting your product, service, or industry need that may appeal to an entire market, Account Based Marketing treats each account as markets in their own right. ABM is personalized marketing on steroids. ABM acknowledges that every person is different and has different viewpoints and when selling to an organization there will be multiple people involved in making the final decision. Therefore, customizing various messages to the buying committee will greatly increase your chances of winning the deal and expediting the sales cycle. Focusing on an account instead of a broad market will lead you to a zero-waste marketing strategy where people you target will be more likely to buy your product. We are flipping the existing sales funnel and putting each account first. If you look at traditional marketing, they first start with attracting as many people as possible, then they send them emails, and identify interested people. ABM does the opposite, first, we identify the target people and buying committees. Then we engage people with personalized messages and build long-lasting relationships that lead to more new opportunities. By focusing on the individual in the buying committee you are focused on quality outreach and relationship building that generate results. So instead of creating blog posts after blog posts, blasting emails, and buying ads all created for a mass audience, ABM best practices revolve around creating content and crafting journeys for particular people and buying committees. Account Based Marketing also goes beyond just focusing on lead generation. Marketing and sales teams can focus on the individual and encourage up-selling and cross-selling opportunities to get the most value from sales efforts. Focusing the attention of your sales and marketing on an account is not new. Successful sales and marketing teams are used to focusing on an account-level for a long time. Teams who have alignment between sales, sales development, marketing, customer success, finance, product, engineering, and executives will with no doubt be more successful than those that do not. ABM's methods are built based upon principles successful companies have used to grow their business and companies who deploy ABM can quickly adapt these best practices and align their organization towards greater success.

Successful businesses nowadays are using digital tools to expand and track the conversion of each of their media platforms and websites. The efforts that you put in building your personal brand will determine the growth value of your career. Branding, in marketing, is the strategy that produces real results over the course of months, years and decades. Its main characteristics are slow, traditional and long term benefits. Just like in successful companies, a trusted brand brings new customers in large numbers, a trusted personal brand will boost the number of job opportunities you receive and scale your career. There are different strategies growing businesses are using to strengthen their brands, in this article, you can learn the pillars and tips you need to expand your personal brand. Content Authority. The best way to establish and strengthen any brand is through content.  Best well-known brands are the ones with lots of engaging content. In the case of your professional life, your content is what differentiates you from the rest. For example, your resume, your professional experience, your skills, your achievements, your mission, and your goals. Once you are sure your content is engageable and strong, you can think of building an expandable personal brand. Use Social Media. If your content is great, is useless if no one can find it. Large companies are changing their recruiting formats, now is the time to join a recruiting software platform and to make connections with those who will contribute to the process of expanding your personal brand. You need not only to have good content but also make it reachable. Don’t consider just using one single digital platform, you need to be everywhere where you can find potential growth. Here is a list of the top ten recruiting software platforms. https://www.cio.com/article/3171728/top-10-recruiting-software-platforms.html Become a prolific guest blogger. For brands with a clearly defined audience, guest blogging is one of the best ways to put your content in front of responsive. Successful companies, in their digital marketing campaigns, always have a clearly defined target to avoid wasting time and efforts on practices that won’t cause any benefit. As you expand your personal brand, you need to do the same, have a target audience. In this situation, your target audience can be the company where you want to work next, someone who you are interested in doing business with, or any other recruiter. Guest blogging allows you to make real connections and generate a large number of conversions and it can be as simple as sharing someone’s content or thanking them for their great article. Keep your content and image consistent. Once you have gathered all your content make sure you keep it consistent and with the same focus. If you keep redirecting your career every few years by choosing different paths, is going to take you a long time to reach for success. It is not impossible, but you might have to start all over again many times. Build your career through consistency. Making your portfolio to look sharp and focused is going to build trust in the potential people who you can do business with. Remember to always show your passion and purpose. Think long-term, branding results aren’t immediate. While you continue to expand your personal brand remember your focus is on building a strong brand to have a larger success. If you just focus on the immediate results, and when you do this, you can either stop the progress you have built or lose motivation. ”Branding is like a wave - what begins as a small ripple grows into something much larger and more powerful as it picks up momentum” -Sophia Smith. Pull the plug on your branding efforts too early and it will never reach its full potential. Just like a strong brand is a powerful asset for any business, a personal brand is also very powerful for your career. This article was inspired by the ideas of Sophia Elizabeth Smith in her article “7 digital Tips to Expand Your Brand Presence and Reach” https://digitalmarkehttps://digitalmarketinginstitute.com/ and also by the blog post of Jeff Bullas called “The 10 pillars to Creating a Personal Brand in a Digital World”. https://www.jeffbullas.com/