Author: James Riseman

Thanks to Kaushik Patel (Sr. Director of Online Marketing & Marketing Operations at ThoughtSpot), Shari Johnston (SVP of Marketing at Radius), and Josh Hill (Marketing Automation Leader at RingCentral) for an informative panel discussion/ workshop on March 28 on the MarTech Stack. Below are some notes and video snippets from that discussion, and here’s the slides:

James Riseman (host intro): Welcome to 3^rd SF Demand Generation and Marketing Operations Meetup. Marketing has changed tremendously over the past 15 years. With the explosion of marketing- and customer-related data and MarTech systems, it’s much easier to leverage data for effective marketing campaigns and measure the impact of those campaigns. The people in Marketing are evolving too, and we’re seeing more quantitative- and systems-focused marketers than in the past. Our panelists are great examples of this new breed of quantitative-/ system-oriented marketers.

Kaushik Patel (2:00): ThoughtSpot sells to the business intelligence (BI) persona in companies. ThoughtSpot has been focused on how to reach and sell to this persona.

Kaushik has developed a vision around transparency. He strives to give each account representative a snapshot into who they’re targeting. He created a MarTech stack to give the ultimate visibility to account representatives and effectively target those accounts. The MarTech stack will change as ThoughtSpot evolves and its sales and marketing needs change.

(9:00) He reviews the tech stack and vendor options every couple weeks. Uses ZenIQ to ensure they have the right, relevant contacts covered at each target account. Kaushik has 80% coverage of the key personas across ThoughtSpot’s entire target market, and his team reviews this on a quarterly basis.

LeanData is an important part of ThoughtSpot’s stack, so they can effectively do account mapping. Predictive analytics didn’t work for ThoughtSpot because they didn’t have a long history of sales. ThoughtSpot has done some customization of Salesforce so they can assign accounts to representatives effectively.

Audience Question (13:00): Why are you using tools like Data.com for data enrichment when you have Demandbase?

Kaushik: ThoughtSpot uses Demandbase only for form enrichment, and uses Data.com, DiscoverOrg and other tools for data enrichment.

Audience Question (14:00): How did you start your MarTech stack?

Kaushik: Started to build stack in 2015 with Salesforce, Marketo and LeanData. Started with LeanData because they wanted to do account-based routing from Day 1.

Audience Question (17:00): What tools work best for you for lead generation and targeting?

Kaushik: LinkedIn is working really well.

Audience Question (18:00): What percentage of your Marketing spend goes towards the MarTech stack?

Kaushik: About 6%

Shari Johnston (19:00): Started developing the Radius MarTech stack with a focus on how its customers buy. There is no single channel that persuades customers like Amazon to purchase Radius; it’s a complex path.

Radius uses an Account-based marketing approach. They have 2 full-time people as well as an agency to deliver on its MarTech and Demand Generation implementations.

Audience Question (25:00): What marketing channels work best for you for lead generation?

Shari: Radius has a long and complex sales cycle. Security, Marketing Operations and other personas are involved. The sales cycle involves a lot of in-person education, so events have been working really well.

Audience Question (27:00): What are the most important tools for your demand generation efforts?

Shari: LinkedIn, Marketo, Salesforce, LeanData and Slack have been working really well.

Audience Question (29:00): Have you analyzed the effectiveness of your various marketing channels?

Shari: Breaks out marketing divisions into field/ events, demand generation and digital marketing. Field marketing has outperformed the other channels.

Audience Question (30:00): What’s your biggest pain point as a CMO?

Shari: It’s always a challenge to manage leads and data effectively, and make sure leads aren’t dropping. A lot of technology investments involve solving problems within Salesforce.

Audience Question (30:00): What are your secrets for successful events?

Shari: Radius has a “go big or go home” philosophy around events. We usually have a big presence at events or none at all. We also like to host “home grown” events in different localities. Also, direct mail has done really well for us. We use PFL quite a bit.

Josh Hill (32:00): RingCentral has a “big machine” around lead generation, and employs 30-40 people in demand generation. RingCentral has historically targeted SMB companies, but is migrating towards account-based marketing as it targets more enterprise companies.

Josh (41:00): It’s important to think about the buyer-/ customer-centric journey as you construct your MarTech stack. If you start from the vendor-/IT-specific perspective, you’re probably looking at it from a different perspective than your customers. Customers don’t think in terms of funnels for instance.

Kaushik (45:00): Marketing in the BI space is a completely different animal. Very few BI professionals are actively looking to replace their BI system. Most the people doing searches on BI (business intelligence) are academics and students. It’s important to set up your MarTech stack with your buyer cycle in mind. Also, the personas we target are completely left-brained/ analytical. At BlueJeans, I could nurture leads in a more standard way, but at ThoughtSpot, I have to be mindful of this very different buyer and buyer journey.

Audience Question (49:00): How do you define your total addressable market and identify good market segments?

Kaushik: In the BI space, you can look at analysts like Gartner, who will say it’s a $70 billion market for instance, and 30% is product-related. You can also search titles in LinkedIn to get a sense of the number of people involved and the spend. We struggle with the best approach.

Shari (51:00): We do TAM analysis for a lot of our customers, and since they’re US-based businesses, we’re able to slice and dice the data effectively.

Audience Question (52:00): Where do you recommend that the MarTech work sits, within Marketing or Sales?

Shari: We have it sit within the Demand Gen and Marketing Operations teams. That arrangement works well.

Kaushik (51:00): We also have it sit within Marketing; I don’t think Sales would be as well-suited to manage the MarTech stack.

Audience Question (53:00): What success metrics do you utilize?

Shari: Our primary goal is pipeline generation, as measured in dollars.

Kaushik: We get measured on everything we contribute to the pipeline. Because of the nature of our product and the analytics our team wants to run, everything we do has to be available to analysis.

Audience Question (56:00): What portion of closed business do you think your team has a significant impact on?

Shari: We do 30-40% of sourcing for the pipeline. In terms of influencing the buyers’ journey, we influence more than 90% of deals.

Kaushik: We drive about 70% of sourcing for the pipeline right now, but that will change as ThoughtSpot matures. At BlueJeans, we would measure both sourcing and closure, and analyze what we directly influenced versus what was channel influenced.

Sponsored by:

Thanks to Bonnie Crater (CEO at Full Circle Insights), Charlie Liang (Director of Marketing at Engagio), and Dayna Rothman (VP of Marketing at BrightFunnel) for a lively panel discussion on January 17 around Marketing Attribution. Below are some notes and video snippets from that discussion:

James: What is Marketing Attribution and what types of companies is it good for?

Bonnie (2:00): Marketing attribution helps connect campaigns to revenue. How do campaigns contribute to sales? At the end of the day, we’re trying to make better businesses and optimize our marketing spend.

Dayna: Connects touches on buyer journey. See what’s accelerating people through the funnel. What is the journey your personas go through, so you can understand what’s working and what’s not. It’s a very data-driven way to run marketing in your organization. Marketing budgets are very large. Even a 5% optimization can move the revenue needle a big amount.

Charlie: Marketing attribution as a marketing tactic answers the questions: Are my marketing dollars driving a return to business results? Am I spending the right amount of resources on the programs that matter?

James: Do you need Salesforce to make marketing attribution work?

Bonnie (5:20): As a former 5x VP of Marketing… You want to get close as possible to sales team, by having apps living inside the sales platform, so both sales and marketing can see this data. If data is in a separate system that sales can’t access, it’s hard for them (and marketing) to have good conversations. If you have Marketing look at one set of information, and Sales looking at another set of information, then you’re not having good conversations.

Dayna:  The BrightFunnel platform is outside of Salesforce. We pull info from Salesforce, Adwords. Not every marketer has access to Salesforce or has a Salesforce login. At Marketo, half the marketing team didn’t have Salesforce logins.  It’s important to have data available to sales team, and to board members. Important to have a process about disemminating that information, whether it’s weekly meetings or dashboards or within Salesforce. It’s the communication that is key.

Charlie: Salesforce was invented over 15 years ago. The system shouldn’t drive the business results. The system doesn’t matter as long as you’re getting what you need for your business; even Excel could work.

James: What size companies need marketing attribution?

Bonnie (10:00): Startups don’t need marketing attribution. Need to be doing enough marketing to compare results. Less than $400,000 a year, you don’t need marketing attribution. Have to be doing marketing, have a team, and getting enough information to optimize your marketing budget.

Dayna: Everything at Marketo is driven by data. How am I going to track all these programs I am managing, even though we [at Everstring] are small. When you’re first building the machine, you need to know what works and doesn’t, especially if you can’t waste resources. It’s all but impossible to measure multi-touch attribution without a system; at a minimum, start thinking about and planning for attribution even when you’re small.

Charlie: Account-based metrics are different from a lead gen-based model. When I was using a lead gen-based model, I had a huge Excel spreadsheet. At Engagio, we look at a roughly 50-50 split between inbound and outbound. Are efforts to target accounts getting us in front of the right people at those accounts. We measure the Engagement minutes that lead to a marketing qualified account.

Bonnie (17:00): Response based marketing is a traditional marketing approach. Most B-to-B marketers have been working this way. The new idea is account-based marketing/ targeting strategic accounts. Marketing now focuses campaigns on these strategic accounts with the benefit of targeted systems. Companies really need both ABM and response-based marketing, as well as systems that measure marketing campaigns for strategic accounts. Response-based marketing reaches more broadly.

James: What’s your advice for a smaller company/ startup for supporting marketing attribution?

Dayna (20:00): It’s important that every program be measurable and that you understand your success metrics now; they may change in the future. KPI changes for every channel, ads vs. emails vs. events. Also, building a culture of measurement in team and organization. Make sure everyone knows what measurement is, what attribution is, what we measure, how to look at programs in a more strategic way, “eg. what is quality of these 100 leads.” Manage up: Move away from vanity number metrics (eg. leads). But train the board and train the CEO and the sales VP on how to look at right times of measurement. Be very specific about money spent, results, and buyer journey.

Charlie: Don’t start with what’s the ROI of marketing. Start with a problem set. What are you trying to do? Get meetings? Accelerate the deal cycle? The marketing mix will be different for a specific program set.

Bad data is worse than no data. How do we give credit to what? How do you know which of the 5 models is the best model? Charlie likes “Engagement Minutes” – for example, some account got 5 engagement minutes because they read this white paper. It’s more accurate than assigning lead scores.

James: What are some examples where marketing attribution has worked well, and a company has figured out a more optimal marketing mix?

Bonnie (25:00): I like the first Sirius Decisions Model. It provides a simple way to measure volume, velocity and conversion through the funnel. It helps identify trends and problem areas (e.g., marketing to sales handoff). It also helps with budgeting, and knowing what the sales volume was.

Marketing attribution is for optimizing the marketing budget, and for improving campaigns that are driving revenue. First touch, last touch, and multi-touch metrics are all important. First Touch is very important for a start-up. If you’re a bigger company, last touch can be more important. With Marketing Attribution, Sales and marketing are one line on the P&L, so this helps with collaboration.

Jobvite was a great smaller customer, when they were looking for their Series C. They decided to align across the marketing funnel. They identified processes and prioritized marketing budget. Jobvite doubled their productivity from same budget; they doubled leads and doubled revenue by analyzing the impact across the marketing mix.

Audience Q+A (30:00): What is an Engagement Minute?

Charlie: Lead scoring is arbitrary. Engagement minutes are less arbitrary. For example, a demo at our booth at Dreamforce could take 30 minutes. A Webinar could take 60 minutes. An Engagement Minute measures how long a person or an account spends with your brand. When they exceed a certain number of Engagement Minutes, then they are tagged as a Marketing Qualified Account (MQA).

Measure their activity. If 20 people consume 5 campaigns, how do you give credit to sales for all these different touches?

Audience Q+A (32:40): What evidence do you have that Engagement Minutes are a good measurement, as some people make quicker decisions than others?

Charlie: We ask our sales team: “If a marketing manager from a 250-person watched our webinar, would you want to follow up with that person? If the answer is Yes, then that is a MQA. By definition, a MQA is someone Sales wants to follow up with.

Audience Q+A (36:00): Sales Reps typically do not show too much discipline within Salesforce. If Sales Reps aren’t notating the account or campaign information in the right way, how can you accurately measure Marketing Attribution?

Dayna: We combine sales and marketing, which is unusual. We’ve done a lot of training with sales reps to get them to use Salesforce to get them to attribute different things. We did assign different % in model that were more brand focused vs. closed revenue and opportunities.  Do you have web tracking, to track those first touches, when you’re thinking about what’s brand and what’s directly related to revenue.

Bonnie: I want to get back to this Engagement Minute thing… What’s the difference between a “score” and a “minute”?

Audience Member: With minutes, I can isolate it: minutes only for trade show, for this email. Don’t need an attribution program to know how we accumulate these numbers.

Charlie: Engagement minutes is measured at the account level. Engagement Minutes measure attention span, whereas lead scoring is a black box.

Bonnie (41:30): Lead score and Engagement Minutes seem to be effectively the same thing – they’re both just numbers that are assigned.

Audience Q+A (42:30): How do you account for overlap between a tradeshow, Facebook, PR?

Dayna: You can create different attribution models depending on the weighting you choose. Some clients use equal weighting, or “toggle” weights based on what they know. Some do 40-20-40 weighting (first – middle – last touch). At Brightfunnel, we’re thinking about using machine learning for these models in the future. It could look historically at what programs have worked best to drive revenue.

Bonnie (46:00): You should select a model for a reason. For example, you can make a top-of-the-funnel weighting if that’s important to you. You’re often discovering how your business actually works with marketing attribution. Machine Learning will not be a panacea because everything is changing; history cannot predict what will work this year.

Thanks to Lisa LaMagna for sharing notes, and to our sponsors for this great panel!

Chat and MarTech Integrations Drive Better Customer Experience, and Increase Sales

As many readers know, Udacity is a leader in the online education industry. Udacity has trained over 10 million students worldwide in over 160 countries. They also partner with over 50 enterprise clients and 200 industry partners to encourage high-quality employee training on the latest technologies, processes, and concepts.

When Scott K. Wilder joined Udacity last year as their Head of Lifecycle, Growth and Performance Marketing, he was tasked with global customer growth, acquisition, and user engagement across Marketing channels and the customer journey. On the Marketing systems side, Udacity was in a slightly “Wild West” state — Scott saw many opportunities to improve business processes, create company wide-dashboards, and improve revenue stack integrations.

Scott initially focused on installing effective MarTech systems, integrating across systems, and putting necessary processes in place. On the MarTech side, Udacity invested in several vendors, including Intercom, Blueshift, Salesforce, Amplitude, Calendly, and Segment:

MarTech System Evolution

Rather than try and boil the whole technology stack “ocean” at once, however, Udacity focused on one or two key MarTech areas every month. Trying to boil the whole tech stack ocean at one time can overwhelm effective implementation. Instead, Scott leveraged a Minimal Viable Product (MVP) approach, learned, and then scaled after 15 – 30 days of testing. Too many companies, he told me, try to launch with every use case addressed. As he learned from his 10 years at Intuit, focus on the critical few use cases first.

On the integration side, the Udacity team ensured that specific “hub” systems had timely access to all relevant data. For example, the Marketing team gained access to a customer’s identity and Website activity prior to an Intercom chat, so the conversation could be as personalized and relevant as possible. Imagine someone greeting you and saying “I noticed you were looking at our AI courses. Are you an AI Developer or AI Product Manager?” The Salesforce system gained access to this Web data as well as chat records, so other customer interactions such as phone calls, triggered emails, etc., could be highly customized.

To stitch all these systems together, the team leveraged not only Segment.io, but also Fivetran to ensure that Marketing data is uploaded into AWS Redshift. There, analysts and executives can query their data, and develop dashboards in Chartio to deeply understand Udacity’s business and customers.

Udacity MarTech Integrations

On the process side, the Udacity team first addressed the low-hanging fruit, and got the most out of their Intercom instance by mapping automated bots and live chats to the acquisition, engagement and retention parts of the funnel. Scott’s team also instituted stringent SLAs for response times, so every customer would receive a chat response within 2 minutes. Finally, they then took the big step of centralizing customer conversation feedback, and integrating all customer conversation channels, including Intercom and Zendesk, into one place. Udacity created a SWAT team that would regularly search through all customer conversations, read them verbatim, and conduct analyses. This team could then monitor feedback changes over time, receive alerts when anomalies appear, and monitor the overall pulse of customer interactions.

Intercom Chat Inbox, with Qualification Details

With these modifications, chat has been a big success at Udacity. Chat is used throughout each stage of the customer lifecycle now, from the initial meet and greet, to classroom discussions, to career services. In addition, each customer segment has different chat messages during their respective customer journey. Chat has been so successful at Udacity in large part because younger generations are accustomed to communicating this way. It is also relatively easy to scale, and enable Sales, Marketing and Customer Success to reach more people on a real-time personalized basis in less time. As a result, Chat is driving a significant part of the company’s revenue.

Customer Chat About Potential Course

It hasn’t all been easy, though. There are challenges to successfully implementing chat systems as well. For example, it’s highly important to set customer expectations appropriately. Udacity cannot always respond to a customer’s chat question in real-time, and without proper expectation setting, that could result in a poor customer experience. Misset expectations around real-time responses can also result in customers posting the same chat multiple time. Geographic sensitivity is also important – the tone used, British English vs. American English spelling, etc.

Udacity has realized tremendous gains with its chat and MarTech systems efforts. Scott would emphasize the following lessons learned for other MarTech practitioners who want to introduce chat:

• Focus on profitable parts of your Website first. If you can quickly improve customer conversions, revenue, customer satisfaction, and/or other measurable metrics, your initiative will gain broad support.
• Centralize feedback from customer conversation channels, like Intercom and Zendesk. This will help you consistently measure the “pulse” of your customer interactions.
• Conduct Deep Dives into issues by searching through all customer conversations and reading them.
• Roll out Integrations Slowly: The Segment.io/ Website, Salesforce, and Fivetran/ analytics integrations have added a lot of value. But don’t boil the ocean, or you will get overwhelmed. Focus on smaller integrations initially that you can quickly complete.
• Leverage Automation: Finally, create custom bots so that customers can still interact with chat after hours.

Finally, Wilder believes improving chat should be thought of as a learning journey. Each conversation offers an opportunity to understand your customers better.

 Achieved Nearly 50% Increase in Conversions

In 2011, two major Lake Tahoe resorts, Squaw Valley and Alpine Meadows, merged. In 2013, the resorts proceeded to integrate their Websites, branding, messaging, and overall marketing efforts. During this time, the team revisited the marketing strategy and worked with an agency to improve persona-targeting as well.

The Squaw Alpine Team identified four personas – Beginners, Family, Destination Travelers, and Passholders – and brought these personas to life with a very personalized, improved Website experience. Users are identified through three different ways: self identification, web behavior and CRM capabilities. They are then served relevant content throughout their web experience, and that shows the relevant benefits of visiting the resort.

Last year, Squaw Alpine began to work with Evergage, a Website personalization tool. Within a few weeks, they were able to fully realize these very personalized experiences for online visitors, and even greet Passholders by first name on the Website.

Home Page for the Family Persona

The improved, personalized Website in conjunction with other marketing efforts has resulted in significantly higher revenue and conversion rates compared to the earlier siloed Website experience:

• 83% lift in revenue and a 47% lift in conversions (online purchases) for Destination Travelers;
• 41% lift in revenue and a 38% lift in conversions for Families; and
• 45% lift in goal completion (renew season pass) for Passholders.

Squaw Alpine has leveraged specialized marketing technology and approaches in other ways to grow their unique, weather-dependent business. They work with an agency on display ads and media. The agency supports very flexible media spending, so Squaw Alpine can postpone any ad campaigns until there is a snow event.

Squaw Alpine has pulled live Webcam feeds into their Web banners and email campaigns. Webcam-based creatives have driven 92% more in direct revenue versus a standard “new snow” banner ad. The team has also set up a weather trigger campaign in Evergage. After a Web visitor views the snow report page two or more times, they are offered an opportunity to subscribe to a daily snow report, sent directly to their email inbox every morning. The team also set up a “Powder alert” email campaign that automatically runs when the resort receives four or more inches of snow. These data capture campaigns with weather triggers, has lead to a 40.2% increase in Web email subscribers.

One of Squaw-Alpine’s Webcams

The team is also very excited about the launch of their new mobile application available for iPhone, Android and wearable devices. The new Squaw Valley Alpine Meadows app will let users do everything from finding friends on the mountain, to seeing which lifts have the shortest wait times, to calculating a user’s entire ski season’s worth of vertical feet skied. You can also view the resort’s Webcams in this app.

The New Mobile App

The merger of Squaw and Alpine’s brand, combined with the persona-based communications and investments in MarTech, have enabled the team to successfully maximize KPIs such as increases in revenue, engagement and retention. The Squaw Alpine marketing team is truly shredding it.

Jackie Megnin is the Web and Social Media Manager at Squaw Alpine. James Riseman is a Principal at MarTech Review.

Lessons on How Belly Retooled its MarTech Systems and Processes to Increase Leads by 125% and Close Rates by 30%

Belly is a high-growth company based in Chicago. It was founded in 2011 as a technology company focused on enhancing customer loyalty for small and medium-sized businesses, like coffee shops, retailers and dry cleaners. Belly has helped over 10,000 businesses serve loyalty rewards programs to about 8 million consumers with its iPad and mobile-based solutions. It’s a “two-sided” network that serves both businesses and consumers (those businesses’ Members).

Belly landed its initial customers with outside sales and “feet on the street.” By 2015, Belly had gained a significant market presence, and shifted from a dominant outside sales team to a dominant inside sales team. We de-emphasized cold calls, and invested heavily in Web-based leads for this transition. We found that customer acquisition costs were 30% lower with inside sales than outside sales, and that inside sales were more willing to properly use CRM (Salesforce), giving Marketing more control. However, the shift to inside sales required that we retool our marketing and sales systems to optimize the sales process.

Over the past year, we have made significant progress in growing our inside sales team, and retooling our technologies and processes to grow leads and sales. We have seen a 125% increase in total lead volume over last year, and a 30% improvement in deal close rates. In this blog, we will be sharing details about how we increased our leads and sales effectiveness. We have engaged a number of techniques and technologies to achieve this, including:

• HubSpot for Website forms and marketing automation;
• SendBloom for email lead nurturing campaigns;
• OpenSoon and other 3rd party data providers for contact information on brick & mortar companies that will open in 3-12 months;
• Salesforce for overall business sales and lead tracking;
• Infer for lead scoring and management (predictive analytics); and
• InsideSales for lead operations.

This blog is most relevant to B-to-B marketers, especially within high-growth companies.

GROWING LEADS WITH DIGITAL MARKETING

By the time Belly had gained more market presence in 2015, we decided it was time to invest more in inside sales. Rather than focusing on cold calling, we invested in modern digital marketing practices to find and grow leads.

We started working with 3rd party data providers, including OpenSoon, to identify good prospective business customers. OpenSoon provides data on brick and mortar companies that will open in 3-12 months. Now when we receive information on an emerging business, we use SendBloom to reach these prospects with attractive, informative emails. The “call to action” is typically a response from the new business requesting a Belly demo. Each email is associated with a specific inside sales representative, who can provide a demo or other follow-up information upon request from the prospect. Once we show a demo to a prospect, the close rate is generally very good – over 40%. But the response rate (as measured by demo requests) on SendBloom emails to OpenSoon prospects is only around 2%. We continue to work with other 3rd party data providers to find the highest conversion.

We also invested significantly in the design and optimization of our Website to attract and convert relevant small business prospects to request a demo of Belly. We use HubSpot for the Website forms themselves, and Optimizely to find the best format:

When a prospect visits our Website and fills out a HubSpot form, they are converted into a lead and pushed into Salesforce. We engage these leads by enrolling them into a “prospect journey” that includes a pre-defined series of phone calls and educational emails from our inside sales representatives.  The educational emails and persistent followup has allowed us to convert about 10% of prospects that originated from the Website into paying customers.

BELLY’S LEAD GENERATION AND MANAGEMENT STACK

We continue to experiment with new approaches and programs to drive more quality leads. For example, we are working to iterate on our current referral program; an initiative that started during an internal “design sprint.” The customers we gain through referrals have over a $600 higher LTV (lifetime value) than non-referrals. We are also using paid search and experimenting with programmatic display through QuantCast. We also continue to invest in content including webinars, blog posts, white papers and video. In addition, we just launched a new way for prospective Merchants to buy Belly right from the web, without having to talk to an inside sales representative. We are focused on educating our prospects and giving them the tools they need to make a buying decision. How they buy should be up to them. From user testing, some folks prefer to buy without having to talk to someone.

MAKING INSIDE SALES MORE EFFICIENT WITH LEAD SCORING

Belly also invested in several new processes and systems to make inside sales more effective, including lead scoring. After a lead is pushed into Salesforce, it is given a lead score with Infer, a predictive analytics vendor. Belly uses two lead score models:

1. Predictive lead score model/ likelihood of closing. Infer assigns the lead a number, from 0 to 100, and also buckets the lead into a letter ranking, from A to D that corresponds with the lead number. The Belly inside sales team have found leads in the “A” group 4.2 times more likely to close. Infer uses its own proprietary system/ data to evaluate multiple attributes from each lead (e.g., the email domain, the FaceBook page status, and the zip code) to arrive at the lead score.
2. Lead qualification. Belly created a secondary model with Infer’s help to assess if a lead is qualified for Belly’s services. Mainly this model evaluates the lead’s geographic qualifications, as Belly only operates in the US and Canada. This model also uses lookalike models based on earlier, unqualified leads in Salesforce.

Lead scoring through Infer has been a game-changer for us. It allows sales to prioritize their outreach and it allows marketing to have a deeper understanding of our ideal customers, so we can find new ways to get in front of them.

Belly also invested in InsideSales.com to manage the sales workflow for each lead. Belly distributes each lead to a sales representative for follow-up through InsideSales.com. Since building this lead scoring and management system, the close rate per sales representative has increased 30%. Our inside sales lead management systems look like this, where Infer is scoring/ categorizing leads, and Salesforce CRM acts as our leads “platform”:

With a lot of experimentation, measurement and adjustments, Belly has established effective inside sales systems and processes. We never stop improving. We’re always looking for ways to improve our performance, either by growing our top of the funnel lead volume, or optimizing our current sales processes to increase our conversion rate further down the funnel.

Lauren Licata is a Vice President of Marketing at Belly. James Riseman is a Principal at MarTech Review.

Lessons from Using a Smorgasbord of Approaches including Content Marketing, Social Marketing, Lead Generation, and Predictive Analytics

Social Tables is a high-growth company based in Washington, DC. It was founded in 2011 as a cloud-based event management software platform. Social Tables has helped venues and event planners work more collaboratively and efficiently together to plan over 1,000,000 events to date.

With our free mobile applications and 14-day free trial on our Website, we had figured out a way to consistently generate about 1400 leads per month. The Business Development team would pursue most of these leads, but they were often not great. They could be international leads (in markets we do not support), or leads from smaller event planners or venues where the transaction would be too small to justify an extensive sales effort.

In this blog, we will be sharing details about how we increased leads from 1400 to over 6000 per month, and then how we started managing those leads for maximum efficiency and impact. We used a number of techniques and technologies to achieve this, including:

• Whitepapers and new mobile applications on the content side;
• Facebook and Twitter advertising;
• Deep analyses with Excel’s Stat Pack to assess the value of different types of leads;
• Lead scoring and management with Infer (predictive analytics), Velocify (lead operations), Pardot, and Salesforce;
• A full Marketing Technology stack for improved operations, including C3 Metrics; and
• An online (aka, “low-touch”) sales model for smaller leads.

This blog is most relevant to B-to-B marketers, especially within high-growth companies.

GROWING LEADS WITH CONTENT AND SOCIAL MARKETING

In 2015, we introduced some innovative new content, including:

• A popular, free mobile application, Site Inspector, that collects and analyzes information on a potential venue during a site visit;
• A paper titled “Little Known Ways to Enhance the Site Visit Process,” co-written with PCMA (Professional Convention Management Association); and
• A paper titled ‘The 9 Ways Meetings Will Impact Hotels in 2016,” co-written with Meetings Mean Business and the Convention Industry Council.

We found that Twitter proved to be a cost-effective way to encourage prospects to check out and download our mobile applications. We also found that Facebook ads efficiently encouraged prospects to sign up online for a free 14-day trial of Social Tables. The combination of the new mobile application, the whitepapers, the association partnerships, and effective social advertising resulted in our monthly new leads quickly growing from 1400 to over 6000!

With this tremendous growth in leads, we experienced some serious challenges. The Business Development team became overwhelmed following up with leads, and the number of “unqualified” leads grew. We did not have enough business development specialists to pursue each lead. Opportunities were slipping through the cracks while we spent time pursuing leads that should have been directed to a low-touch/ online sales approach. Also, we were not purposefully de-prioritizing any leads. If business development could not actively pursue a lead, we continued nurturing that lead through ads and retargeting, as well as our marketing automation system. We were spending a lot of money advertising to unsuitable leads.

ADJUSTING TO MANAGING LEADS EFFECTIVELY

We identified some solutions to these challenges. Regarding the quality of leads and the lack of sufficient contact information, we expanded our registration forms to include fields like “Job Title” and “Phone.” We also modified the form to specify “work” emails:

While these changes were fairly small, they provided more information about the quality of the lead, the location of the lead, and contact information.

Next we initiated some heavy-duty analytics to improve lead quality and flow. We first agreed on goals with the sales team; there was consensus that fewer, higher quality leads would be beneficial to the broader team. We then took all data (in Excel’s Stat Pack) for the past few years, and analyzed the number of opportunities per our four verticals (event planner; and Small, Medium and Large hospitality venue), as well as the revenue generated per opportunity. We found that approximately 70% of revenue comes from hotels and venues. We also found that larger venues typically drive greater revenue and success for Social Tables. Working backwards, we could target the leads that Marketing would need to generate to meet revenue goals.

We then introduced an end-to-end systems approach to operationalize lead management. We already had Salesforce CRM, Pardot, and other elements in place for lead generation, management and marketing automation:

We added some additional data systems to our MarTech stack, including:

• Infer Predictive Analytics/ Predictive Scoring. We created a fit-based Infer Predictive Scoring model to identify and filter prospects based on how well-suited they are for our software. Using internal data from the company’s CRM (Salesforce) and Marketing Automation (Pardot) systems and trial usage, plus new external signals from a variety of outside data sources, like technographic signals and other public data like job openings and web presence, Infer now predicts which leads are most likely to convert to customers.
• Velocify lead management and workflow software. We use Velocify to manage the lead workflow, and effectively transform Infer recommendations into tactics for the business development team.
• C3 Metrics advertising attribution and Salesforce integration. We use C3 Metrics to link front-end advertising campaigns to back-end sales motions.

Now our Lead Nurturing and Lead Management systems look like this, with Infer scoring and categorizing leads, and Salesforce CRM acting as our leads “platform”:

We are making progress toward creating a well-tuned lead generation and lead management “machine,” where smaller leads are fed into a lower-cost lead nurturing and online sales model, and more promising leads are routed to Velocify and our business development team for “high touch” sales. With Infer, Social Tables redefined its definition of marketing-qualified leads (MQLs). We can now efficiently route smaller venues to an online sales model, but keep business development engaged with larger event production companies and larger venues (categorized as “Infer A or B” leads). We created the new MQL definition and the workflow rules within Salesforce.

GOOD MANAGEMENT AND SYSTEMS LEADING TO GREAT RESULTS

Infer, with its predictive scoring, has had a measurable impact on our bottom line. We are now able to save the business development team from wasting time pursuing weak leads. By accurately prioritizing leads, Social Tables has increased our lead conversion rate from 15% to 30%. Our Opportunity pipeline in Salesforce has likewise increased by $500K per month. The business development team is much more productive and happier.

Clearly the Social Tables Marketing team has work left to do. We have seen some big successes with our analytical, systems and process work. We continue to tune our models and systems to optimize performance. With our Infer predictive scoring, we have gained a better sense of high-value customers, and we are now targeting those prospects more effectively with our digital advertising and other marketing campaigns. Finally, Social Tables is focused on tying marketing performance entirely to revenue, and moving away from opportunity or lead volume. We look forward to growing our business further… and trying the rest of our marketing smorgasbord.

Ray Miller is the Senior Marketing Operations Manager at Social Tables. James Riseman is a Principal at MarTech Review.

AVG NUMBER OF MARTECH VENDORS FOR EACH MARKETING DEPT RISING, 2012 TO 2015

Source: Econsultancy, Tealium and Marketing Land

Even as data nerds, New Relic’s marketing team is not immune from the challenges that face marketing departments when it comes to marketing technology (MarTech) and big data. Like many, we can also get overwhelmed by the flood of opportunities, data and new MarTech vendors (according to Scott Brinker of ChiefMarTech, there are now around 3800 MarTech vendors on the market). At New Relic, we have taken a very proactive approach to MarTech, developing a rigorous technology selection, procurement and implementation process, as well as an audit approach for our MarTech tools. In this post, I hope to share a bit on our approach and help out my fellow MarTech nerds.

Start with the big picture: I have heard from numerous marketing colleagues how easy it can be to get lost in the sea of complexity around their big data and MarTech options. At New Relic, we first start with defining the role of MarTech. What goals are we trying to achieve with MarTech and big data? Our Marketing department’s capabilities not only depend on tools, technologies and data, but on people and processes too. We strive to be very goal-oriented with all of our MarTech decisions, and ask questions like:

• How do we get more out of our existing technologies?
• How do we choose the right technologies to add to and enhance our stack?
• How do we partner with the rest of the business to leverage each others’ technologies – with a focus on security and compliance – and foster positive vendor relationships?

Use a technology evaluation framework: At New Relic, we’ve developed a MarTech procurement process, which includes both a MarTech spreadsheet (i.e., inventory of all existing tools at New Relic – built on Google Sheets) and a MarTech request form (i.e., a centralized process to review new tool requests before completing purchase). This procurement approach adds a process layer, but helps avoid inefficiencies, lack of coordination, and wasted dollars. If we already have a technology in-house that someone wants, we can simply connect the requester with the admin for the relevant technology. If we do not have the technology, we speak with a few relevant vendors to understand expectations and required support. We then negotiate with the preferred vendor after this initial assessment.

This process also makes planning around integration and security issues easier. We plan up front to understand if integration resources are required to integrate a new technology with our existing data and broader marketing stack. We also work with Legal and IT/InfoSec before we complete the purchase.

Build an implementation and enablement plan to help ensure a new technology will be successful: At New Relic, we develop an onboarding plan for every new technology. Some technologies are easier than others, and only require a 30-minute phone call with the account manager prior to a successful rollout. Other technologies, especially platform technologies, are more demanding, and require a number of internal stakeholders to come together, as well as periodic check-ins to make them successful. Sometimes these more demanding technologies also require engineering support for integration. Many of the new technologies require that we develop plans around the following:

• Working with the IT organization to implement Single Sign-On (SSO);
• Whitelisting third party sites or APIs with InfoSec for smoother operations; and
• Training, documentation, and often re-training, especially for the more complicated platform technologies.

Conduct regular internal MarTech audits: At New Relic, we conduct regular audits of deployed Marketing Technologies to assess how they perform along criteria such as:

• Criticality – Importance of technology to business operations and goals;
• Fit – Degree to which technology meets user needs;
• Data – Creation, consumption and governance of data within a technology;
• Risk – Probability of loss or uncertainty applied to technology or data it stores;
• Scalability – Capacity of technology to meet current and future business needs;
• Integration – Sharing of data and business processes among technologies or data sources; and
• Engagement – Recognition and maximization of the value of a technology.

In order to maximize efficiency for reviewing various technologies, we take the following approaches:

1. Sit down with key technology leaders; and
2. Conduct an audit survey. For each category of tools, we ask a) How would you rate the value for solving business challenges (aka, functionality)? And b) How often do you use this tool to solve your business challenges (aka, engagement)? We also ask if a user is thinking of evaluating/purchasing new marketing technologies.

Each of New Relic’s 20+ Marketing Technologies are then placed in a evaluation grid, based on these survey results:

The grid’s categories include:

• Extend – We are seeing a lot of value out of this technology. Users are both engaged and seeing good functionality. We will consider ways to expand the number of people using that technology.
• Empower – We are seeing good functionality, but limited user engagement. We will consider additional training for users.
• Evaluate – We are seeing low engagement and value. Can engagement and functionality be increased? If not, we will consider disengaging from the vendor.
• Enhance – We are seeing people frequently using the technology, but it is not providing a ton of value. We will talk to the vendor about purchasing a higher tier of service, or look into ways of integrating the technology to make it more valuable.

The highest scoring technologies along the value/functionality and engagement attributes are usually associated with platform technologies:

In conclusion, the New Relic MarTech strategy is based on creating and leveraging resources to achieving business goals by enabling people to execute processes with the right tools. To do this, we have developed a technology selection, procurement and implementation process. We have also developed an audit approach for our MarTech tools. Please comment below or reach out to me over Twitter @isaacwyatt to share your thoughts.

Isaac Wyatt is Director of Marketing Operations at New Relic. James Riseman also contributed to this post.

Over the last 20-something years, the Internet and smartphones have transformed the art of marketing… several times over.

INTERNET USERS WORLDWIDE:

With the tremendous growth of Internet, smartphone, online video and social media usage, and the digitization of nearly all customer and prospect touchpoints, have come corresponding innovations in marketing, such as:

• Online display ads (1994)
• WebEx/ reliable Webinars (1999)
• Salesforce/ SaaS Customer Relationship Management (1999)
• Google AdWords (2000)
• Facebook Ads (2008)

The early adopters of these and other effective new marketing and sales technologies realized significant competitive advantages. For example, Larry Bartholomew, Lively Lobster’s owner and ad manager, was Google AdWords’ first paying customer. He quickly understood that AdWords could drive more business to his restaurant and help him make money from other sites’ affiliate programs. He grew his affiliate optimization empire to a 16-person business that placed more than $12 million in ads on Google over the next decade. Similarly, early WebEx customers enjoyed sizable gains in productivity and travel savings, as they were able to market and sell to prospects without travel or tradeshows.

The pace of innovation around new marketing technologies is exploding. ChiefMarTech strives to track all the vendors in the marketing technology space. In 2011, there were about 100 vendors listed. In 2015, this exploded to 1876 vendors. And during that time, entirely new marketing technology categories were introduced, including:

• Performance & Attribution
• Dashboards/ Visualization
• Data Management Platforms/ Customer Data Platforms

GROWTH IN MARKETING TECHNOLOGY VENDORS, 2011-2015

And this explosive growth has yet to include newer categories, such as account-based marketing, predictive analytics, and programmatic TV.

While newer marketing technologies frequently offer great promise and Return on Investment (ROI), not every technology offers a great ROI. And even more frequently, most newer technologies present technical implementation challenges before a customer can realize the ROI. For example, one company I know tried to introduce an Account-based Marketing (ABM) system recently, but it was disappointed with the results. The company found that many of the prospects it targets work remotely from the road or a home office (without a VPN). Due to limitations with the Account-based Marketing’s IP-based technology approach, the company was not able to target enough of its prospects to continue its investment in ABM.

Another technology company I know has a product that is embedded in customers’ Websites. The product, like similar competing products, is visible in a Website’s JavaScript tags when it is running on a site. The company planned to run a campaign to target prospects that were running competitive products on their Websites, by utilizing a JavaScript tag-identifying tool. The company was able to identify prospects who had installed competitive products, but they then found that they could not email these companies in a standard manner, like Marketo. They risked having their email server identified as a source of spam if they continued targeting prospects with competitive products through standard email automation approaches.

There is an explosion in marketing technology, and it is not stopping anytime soon. The marketing software market is expected to grow to more than $32.3 billion in 2018, according to IDC, which is up 42% from 2015. Much of this technology can improve your top-line revenue, your operations, your lead nurturing, and so on. MarTech Review, through our reviews and analyses, is here to help you identify the best and most promising MarTech technologies, and support you through the implementation. Join the www.martechreview.com subscriber list to continue receiving our updates on this dynamic industry. And contact us if you want MarTech Review to cover any specific technologies.