Keys to Driving Growth Through Sales and Marketing AnalyticsBryant Lau

Enable Your Sales Team

Good afternoon everyone and thank you all for joining.

Bryant LauDigital Marketing Manager @ HighspotGrowth Focused Demand Gen MarketerHikerDog Owner

Who Am I?About HighspotA single content repository for all of your sales content. Find out why your reps want to use Highspot at highspot.com.

My name is Bryant Lau and for the majority of my career I have had a focus on one problem, how to drive company growth, through sales and marketing analytics. Most recently, I have tackled this problem with my current company, Highspot. Which, provides a Sales Enablement platform that sales reps love to use.

Top 5 Keys to Growth-Driven AnalyticsExamples of Actionable ReportsSummary TakeawaysAgenda

So, for todays presentation, I would like to share how we built a rock-solid analytics foundations and now make key business decisions with confidence.

To begin, I think it is best to first understand the key business decision that we are trying to address.

Where should we invest?Key Question

With the number of tools and technology solutions now available, your demand generation efforts can be measured in countless ways. So, before beginning any analytics project I think it is critical to understand exactly what you are trying to ascertain and the nuances of that question.

The question we are trying to address with our analytics is, Where should we invest?. As a venture-backed company, we have high expectations for company growth and are constantly trying to understand where we should invest, not only money, but also time, to have the highest impact. I like to frame the conversation in this manner as I think there is often an attempt to measure marketing in the same way an accountant might measure an investment. Ill reference this point throughout this presentation.

Now, Where should we Invest? is a rather simple question with a complex answer. So lets take a look at some of the requirements for answering it.

The Right Funnel for YouKISSAlign to sales processWork closely with sales

Key #1: Build a Demand Waterfall

Early in my career, my boss asked me a great question. He said, Bryant are we filling the funnel?. Still fresh out of college I didn't know quite how to answer this, so I answered it to the best of my ability and said, What's a funnel?. Fortunately for me, he saw past that and I ended up learning about the demand waterfall. I'm sure many in this audience are already very familiar with the concept of a demand waterfall but I do want to share a few tips for implementing one. First of all, the acronym KISS applies here more than ever. If you are not familiar with the acronym KISS, it stands for keep it simple stupid. The reason this applies so much to the situation is that as a demand gen team, we often find ourselves working directly with junior sales people who are fresh out of college, and just like my earlier self, probably dont know what a demand waterfall is.

The Highspot FunnelMQL = Ready for SalesSAL = Sales AgreesSEL = Discovery CallSQL = Demo ScheduledOpp = BANT*

*Budget, Authority, Need, Timeline

Key #1: Build a Demand Waterfall

For example, we at Highspot have easily defined stages. An MQL means that we believe it is ready for sales. An SAL means that sales has that has agreed to work the person. An SEL means a Discovery has been scheduled. A SQL means a Demo has been scheduled and an opp requires BANT. What's nice about this process is that it allows us to speak a common language with our sales team and it represents stages that a sales person can easily grasp leaving little ambiguity and rock-solid analytics.

How We started...Two fields per stageBooleanDateUsed MKTO Smart Campaigns to populate fields

Key #2: Measuring Your FunnelBut there were problems...

After implementing a well-defined demand waterfall, we knew we wanted to begin reporting on it. The first way we attempted this was by adding two new fields to our database for each stage of the funnel. The first field would be a Boolean field and it would simply be checked whenever someone enters that stage. The second field would be a date field and this would capture the date that someone entered this stage. We would then populate these fields using smart campaigns in Marketo or workflow rules within Salesforce. Additionally fields like Lead Source, Last Source, and MQL Source, would all be used to capture attribution of funnel activity back to individual programs. At first we thought this was amazing but shortly after implementing it, real-world scenarios made us rethink our model.

Non-linear Sales FunnelWhat happens when a recycled lead/contact has another sales engagement?Capturing multiple entry and exits from Sales Funnel

Key #3: Capturing the Real-world Funnel

For example one limitation of this model is that it does not capture sales processes the way a sales process actually works. As we are all aware, the sales process does not always work in a linear way. Prospects can exit and enter the funnel multiple times. With the data model we had we were only able to capture one sales engagement. This presented an inherent problem, if someone had multiple sales engagements, did we overwrite prior data or did we track them on a separate funnel. Either way, we knew a solution wasnt simple. This problem is only compounded by the default configuration of Salesforce which assumes a prospective customer is only a lead once.

Reporting RequirementsHighly extensibleAbility to edit dataReal-timeAutomated Funnel Progression TrackingAccessible by allReport on entire funnelKey #4: Gathering the Data(Hint: Full Circle Insights does all of this )

The other limitation we found with this model is the inability for anyone to report on it. To try and report on our funnel from Salesforce meant we could run a report on Leads or Contacts but never both in one report. The other challenge is that once a lead has been converted, the lead record becomes locked with no way to ever edit. So, if you ever have a need to add a field you will not be able to report on that field for historical data. Out of all of this, we realized that any solution would need to have very specific reporting requirements:It needed to be highly customizable. I needed the ability to add fields for any analytical purpose.I also needed to be able to edit the data at all times. If I am going to be presenting this data to our executive team as accurate, I need to be able to have full confidence it. And as anyone knows, humans do make mistakes so I have to have a means for correcting the data to ensure the accuracy of the data that I am presenting to our executive team.It has to be available in a report that anyone can access at anytime or else I am going to be spending all my time running reports.

Once I had these items in place, I was finally able to start reporting on data that I can trust. But here, we found another challenge.

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Performance-Driven MarketingCreate hypothesis and apply critical thinkingFailures are valuableFocus on low-hanging fruit & find usual suspectsTribal KnowledgeKey #5: Make the Data Actionable

The data that often comes from analytics systems is often dead. Without context it is meaningless. Looking at the raw numbers from a report provided no detail as to whether that number was good or bad. This led us to adopting a performance-driven marketing culture. That may sound like a fancy word (and it is), but let me give you an example of what that means.

At a previous company, I championed a marketing program that had significant costs (over 20K) and when all was said and done, the company netted zero from it. Now, I doubt I am the only person in the room who has ever done anything like. I think as Marketers we all have done that. And if you have no failures your arent trying hard enough.

The key is to adopt a performance-driven company culture that embraces failures because they are really only failures if you repeat them. It is really best to view each program as a hypothesis, and if it works, great. If not, you are now one idea closer to finding something that is successful.

Over time, this process will contribute to tribal knowledge of what works and what doesnt, so you can build a repeatable and scalable demand generation process.

With these keys to success in mind, lets take a look at some data.#

Attribution via Activation

Activates Sales EngagementGreat fit for ABMExample Reports

This first report is an example of an activation attribution model. With this attribution model we are not trying to understand how a name was acquired but rather what campaigns are resulting in the most effective sales engagements. This is particularly important in the new ABM world that we live in. As ABM often entails acquiring a database for your target personas within your target accounts and then engaging them across a number of channels. With this model, you can now see which programs result in the best sales engagements.#

Example Report - Activation

Here, you can see an example of this type of report. This is fake data but it is very similar to the type of reports that we look at on a regular basis. A couple things to point out:-This data is real-time just requires a refresh. No need to open excel and build reports-It represents both leads and contacts in one report!-It captures the entire funnel in one report

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Example Report - Activation

This puts us in a position to ask the question we started with, Where should we invest?. Well, what we can see from the data is that PPC Campaign #1 performed poorly in November but did well in December. Why is that? What can we do to repeat that? Why did Email Campaign #1 perform well in November but not in December?

Recognizing the success or failure of an individual program allows us to test hypothesis, learn the outcomes, and take an actionable next step for future programs. Again, building a set of tribal knowledge that drives decisions in a data-driven manner.

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Influence - ReportUses a weighted attribution model to measure the contribution from multiple programsBest for measuring programs after a few months have passedCan measure influence across both leads and contactsExample Reports

The next type of attribution model I would like to share is an Influence model. Which is a method that divides campaign responses against the value of an opp. It is highly configurable and can be weighted differently across opportunity roles, contacts, or even leads and contacts for a specific account. Internally, we primarily use an even spread model but additional models can be built as well.

Being that this model looks at opportunities, it is best to wait until a campaign would have had a chance to even contribute to your pipeline. For most businesses this is probably a couple months.#

Example Report - Influence

Again, we are looking at fake data but this particular model is looking at leads & contacts, and campaign responses within 365 days prior to a new business opportunity being created. Looking at this report there are many interesting data points.#

Example Report - Influence

For example, we can see that Roadshows are more efficient at generating pipeline and that Retargeting has been the most effective means of generating closed won business. Having this type of reporting has significantly improved our ability as a company to make the right investments and become a data-driven company.

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Planning & PerformanceMaking the data actionableBecoming a performance-driven marketing team

Example Reports

With the two reports, I know what causes by best sales engagements and I also know what causes my best opportunities. These means we are now empowered to make data-driven decisions and be a performance-driven marketing team. #

Example Report - Planning & performance

For my last example report, I would like to show what I mean by being a performance-driven marketing team. In this report, you can see that we are able to accomplish two things. We can create a report of upcoming programs and know whether or not we have enough programs planned to fill the funnel. This can also be accessed by our sales team so that they can see what upcoming programs we have and what lead flow they can anticipate.We can also measure past campaigns against the original goal that we set for them. This allows us as a demand generation team to learn and adjust our future programs based off of what we have learned with past programs.

This keeps us agile and learning quickly.#

Key TakeawaysAsk the right questionPut data in contextRetain control of your dataRecap

Some parting thoughts before I end todays presentation.Before trying to answer a question, be sure you are answering the right question. This means understanding the nuances and intricacies of a given question in the context of YOUR business. Then, apply this to any solution you are considering to see if they truly address that question. You will be surprised to see the many different ways marketing attribution providers use. The data you generate has to be put in context. If you only ever make business decisions based on reports, you will miss the big picture. What is not represented in reports are people, their decisions, and their reasoning. Those have to all be put in context with the data before attempting to draw any conclusions from it. Personally, I try to maintain a strong working relationship with our ADR team so that I can understand exactly what is represented in the data I am seeing.I have been working on marketing analytics for a few years now at a couple different companies and I have found that the extensibility of a product is a key factor to its success. Each and every company represented here today has a slightly different business process and talks using different terms. It is a simple byproduct of marketing analytics still being a undisciplined science. Thus, your success is dependent on having a solution that can incorporate the intricacies of your business. Simply put, if you dont have control of your data, you dont have control of your business.

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Learn More at Booth #23

Thank You

Thank you all for your time today. If you have any questions, I will be at the Full Circle Insights booth, #23.#