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Martech is About Scale

July 16, 2018 By Josh Hill

Marketing technology is about scale.

Marketers tend to forget this because “scale” isn’t as sexy as Account Based Marketing or funnel reporting. ABM and funnel reporting are not new concepts, and they aren’t new tools.

What is new is the ability to scale up such data collection, reporting, and analysis now that all interactions can be recorded…at scale.

What is new is the ability to rapidly iterate storylines to more segments…at scale.

What is new is the ability to enrich leads and update data mistakes…at scale…without a programmer.

What is new is the ability to predict next best actions…at scale.

When I speak about marketing campaign operations with my team, the question is “How do we scale this rapidly to support more growth?” And if we don’t see the scaling, we re-think the structure of the campaign and even the entire campaign premise to enable scale, or empower a marketer to do more.

If you are considering a martech vendor of any type, I want you to really consider how the vendor empowers you to scale rapidly. One way to avoid “shiny object syndrome” is to ask scaling questions. Another way, is to know what you want. Scaling questions can be internal or external:

  • Can I build templates of assets or workflows?
  • Can I easily map data fields between systems?
  • Do you have an API?
  • How much time does this save me from doing X?
  • Can I automate that?
  • Does this point solution apply to more than one use case? Would I use it a lot?
  • Is there another platform that can do something similar and does more?
  • Are we already doing this, but a different way?
  • Are we running enough of Y to need to pay cash to scale this?

I’m not going to call out any vendors on this. I do see a few interesting point solutions out there that expose certain kinds of data in an automated way, yet do not save so much time that they are worth purchasing because that information could be had with a few smart lists.

Some of the data middleware tools fall into this “is it worth it?” category, especially when the data architecture hasn’t been well planned. What’s the point of a data router if it doesn’t have data flow controls or mapping tools?

Ultimately, look for problems to solve and how to solve them before going shopping.

Filed Under: Marketing Technology

Martech Pricing Models and Market Shift

July 2, 2018 By Josh Hill

Whether you are a martech vendor, or just embracing the subscription economy, your firm relies on a fair pricing model.

Sometimes I see firms start life with a pricing model that made sense then, but now doesn’t make sense as the market shifts.

Data Vendor Renewal Story: Needs Change, Product Stays the Same

Many years ago, I was in charge of renewing our prospect database. I saw we were spending about $29,000 per year for 30 users. Their model was per-user-year plus a level of access to the database.

When I evaluated who really needed access based on real use and interviews internally, I saw we only needed 10 users. I told our salesperson we would reduce our need and I wanted more access to the database. Without even objecting, he reduced our costs to $15,000/yr and gave us more of what we wanted.

That’s great for me and the business, but that vendor just lost $14,000 per year.

Now why did these changes occur in our relationship?

  • staff reduction and organizational changes.
  • reduced budgets.
  • Changed our interaction with data: sales teams hardly use the service while each department was pulling in more data automatically for different purposes. So we don’t need more users, we needed better connections with the data.
  • Needed different data to support growth.

In theory, the salesperson could have sold me on the value, added connectors, and given me unlimited user licenses and instead charged me by the Record Download or profile levels (email, direct dial, etc). And he could have charged me $29,000/yr for that. Maybe I would have gone with that plan if his product accommodated my new needs.

The value to me and the business was effectively the same — the data — so why not just give us unlimited users when we know that most of the usage comes from 10 people? Was the data worth $29,000 per year to us? Perhaps, but not in the way we were asked to use and value it.

What Should You Do About Your Product and Price?

The lesson here is that he was constrained by his Company’s old style product that assumed value was related to the number of user licenses since it was hard to meter value per record back in the day.

Now think about what your clients are telling you? Does it sound familiar? When I was in Sales, I had a strong notion that many renewing clients were not fully satisfied with the database tools we provided. Sometimes their usage had declined or their users had left. Sometimes it was how they wanted to interact with the data. What usually happened was one of four things:

  1. renewal with an increase in content at small fee increase.
  2. reduction in content or price or users.
  3. renewal with reservations and an attempt to build a direct feed or meet their needs in some other way.
  4. cancellation.

The result was we gave away more valuable data without collecting more revenue. The company stagnated. The pricing model and product itself were stuck behind where the market moved to in terms of how they thought about value extraction.

So instead of just accepting a running retreat, why not modify your services and pricing to be where are clients are? It’s a scary move because it is possible to torpedo the business if the transition is not managed well.

Most SaaS subscription services these days are more flexible to keep up with shifting needs and expectations. But not all.

Martech Subscription Models Are In Danger Mode

I hesitate to call out any particular vendor here, but it’s hard for buyers to justify the value certain pricing models deliver. Sometimes it’s challenging because in MOPS, we may not always be able to calculate that value ourselves! Here are the models and pricing issues I am concerned with.

Price per Record

While this is common for databases, it is becoming onerous in Marketing Automation. Old email providers did fee per email, but that led to variable fees that were hard to contain, so pricing record tiers made a lot of sense eight years ago to entice a switch. Now it seems to be a limiter because marketers are loath to delete records, or it’s just hard to do so. What’s the real value of each record when some are Customers, some are MQLs, and some are unmarketable, but could be useful in other ways?

Price per Email Sent

The old ESP model still exists in some areas. This is often sold as email bands, but what’s the value of each email sent when response rates are under 1%? Marketers really have to know their LTV/CAC data.

Price per Add On

Sometimes this is coupled with a feature price with a per record price. I have mixed feelings because some add ons have clear value, while others do not. Always be careful with this one.

Fee per Registration

The fees for many event tool vendors feel opaque. Eventbrite-like vendors who mostly are payment platforms for tickets do well here because there’s a clear merchant fee for credit-card processing and platform. For large scale event tools, the per reg fee is sometimes couple with a platform fee. What’s the real processing cost of the Platform vs. each registrant? What if someone pays $1,000 for a ticket vs. $0? Should I still be charged the same fee? Is that the same amount of work for the vendor’s system?

Fee per Event or Meeting

Vendor charges a flat fee for a tiered event size or number of items used. Sometimes this works, but if the marketer takes advantage of this with lots of large events that technically fit in the buckets, the vendor loses out.

Fee per Feature or Level + User Scale

Smaller martech vendors and tools like LucidChart tend to do this. You get the famous three choices: Lite, Pro, Enterprise where they steer you to Pro in most cases. Really helps to understand your true needs as a buyer to select the right Feature Tier. Often a Feature Tier has a Per User Scale. Many people feel comfortable with this pricing model because we’ve all been trained to use Software License Seats. But not every user is the same and audits frequently find 10-30% of users barely touched it. Slack is famous for attempting to mitigate this on a monthly basis by not charging for unused seats.

For marketing automation platforms, the per user model is outdated. Some users are just API people, and some barely look at the tool.

Fee per MQL or SQL or Per Meeting 

Prospect data vendors and prospecting services will charge for actual value received. I like this, however, it’s difficult to track and remove leads that did not proceed. You have to be very sure of your ability to monitor the funnel with your vendors.

Fee per Computing Power Unit

A variation on the Per Unit model, this is now popular thanks to all the major cloud vendors. AWS in particular combines this with feature sets and database use. I’d like to see Martech vendors use this more because it more accurately reflects the variable costs and real use by marketers. Database costs are incredibly low, so when I’m processing 10 million records for some reason, I want to know it will run quickly. I want to pay for that speed so it doesn’t impact my actual business. Let me know when a martech vendor actually does this.

Now, I understand there are always challenges with metering use as a product ages, but if vendors cannot come up with pricing models which make sense for both parties, someone else will match that need (just like AWS did) and win the business of the future.

Filed Under: Marketing Technology

Working with Martech Vendors – Stop Doing it Wrong

June 27, 2018 By Josh Hill

One of the first posts on this site was the Marketing Automation RFP.

That post was born out of working with my first Marketing Automation RFP where I selected Marketo over Eloqua (and a few others). Having been a salesperson, as well as having worked with many event vendors, meant I had a fairly good idea of how I needed to proceed. Yet, it was still a difficult call to choose one vendor over another when the comparison is fairly close. And it’s still a difficult call. All sorts of human thoughts come into play like:

  • I’ll disappoint the salesperson. They were nice.
  • This better work, otherwise it’s going to be on me.
  • So-and-so wanted vendor X, but vendor Y is really a better bet.
  • I’ve already put so much time into this vendor, it’ll be easier to stay with them (sunk cost fallacy!).

And unless you’ve worked with that vendor before, it is a pretty big bet to commit to a one year contract and tens of thousands of dollars and hundreds of hours of work.

A lot of smaller B2B firms, especially tech B2B, tend to play fast and loose with the many martech vendors out there. Some are super cheap microservices that are easy to swap. Others are much larger investments of time to solve real business scale problems.

When conducting martech vendor evaluations, I see a lot of firms and team members spend very little time evaluating the problem they want to solve and very little time evaluating the vendor. With a few simple rules, you can improve your hit rate with vendors and avoid bad experiences.

Understand Your Needs or You Will Get Sold

The simplest change you can make in your RFP process is to first understand fully your team’s needs. I receive a lot of requests from other marketers that go like this:

“We need vendor X because we’re growing.”

“We need vendor Y because I can’t do spreadsheets anymore.”

Notice that the vendor is already decided here without any particular understanding of the real need. It’s hard to do this, but you MUST push back in a professional, curious way to better understand why your colleagues need a new tool. Be curious, ask questions to fill the answers:

  • Ok, tell me about your spreadsheets.
  • Are your spreadsheets about budgeting?
  • What are you trying to track?
  • What do you do now?
  • Tell me about your growth plans.

Usually there is resistance because these questions are getting in the way of your colleagues’ assumed plans. What you want to end up with is User Stories where you have a sheet or document that says:

As a marketer, I want to know how many registrants I have for event Z within seconds instead of going to 3 different places.

If you are able to do this effectively, you can then explore what may solve that problem or empower the marketer to do this. Many times, existing tools will help a person without purchasing anything. Sometimes it’s just a simple report tweak. Sometimes it’s exploring how an existing tool is used. For example, one need was to more easily deploy a small roadshow with a more flexible page layout. All we had to do was recode a page and Program Token to empower the marketer — no tool required!

Of course, your exploration of the needs will also translate into requirements and features, features you may not have right now. That’s when you compile the needs and can more effectively look outside the organization for a solution. Without this needs list, you will just see shiny objects everywhere.

Remember, it is the salesperson’s job to sell you, or “educate” you, on their services and vision. If you aren’t sure where you want to go, you will be sold on the vision that may not be a real solution to your needs.

Sales Responsiveness Matters

Sales responsiveness matters because it is an indicator of the culture of the firm and if they will care about you after the contract is signed, whether that’s Customer Success, Implementation, Support, or Roadmap – do they care about your business?

If there’s any feeling they do not care, best to drop them from the shortlist. Seriously. No regrets.

One of my core values is service, and as a salesperson, service meant picking up the phone in under 2 rings or responding to email quickly. I evaluate every vendor on this type of responsiveness.

In my first RFP process with marketing automation, it was hard to select a vendor! There were the usual 6 main choices to research—companies that you would feel, on the surface, are safe choices. I was concerned with how scalable the system was; would it work with our systems? Would I be able to make it work? Would other people adopt it? Would it be a quick project or longer? If this worked, would I advance my career? If it didn’t, how would I fix it?

As a marketer or salesperson, these are the hidden questions you, and your prospects and clients are asking. Find a way to answer them in the most appropriate way. The flip side is that you are asking these questions too when buying new martech, so remember how this all works!

Now you have to get a martech vendor to respond to you. This is surprisingly difficult. You have to show the right behaviors and reach their MQL/SQL thresholds to reach a real person. It is amazing how hard it is to have a company respond to a request such as

“I am selecting a Marketing Automation vendor for my company. I have $3,000 per month to spend. I will be your main contact and will recommend you to my manager. Please call me to discuss pricing and provide a demonstration. Please fill out my RFP.”

Some companies will never respond. WTF? When I was looking for marketing automation vendors, a couple of vendors responded with a quick demo, but when I asked for further details, I never heard back. One person actually wanted to not demo the service when I told her I was unable to pay $5,000 per month in the first months of the contract. She never even wanted to negotiate. Other vendors made me go through their junior SDRs to qualify me for the Account Executive. I found that frustrating because it meant repeating my needs to two or three different people before getting a demo.

One vendor I called several times to discuss how to go to the next stage. When I finally got him on the phone, I was told that “we were in our month end closing and I was busy.” So this guy just told me that new business wasn’t important enough for him to even let me know he needed time. Unsurprisingly, that MAP vendor went out of business years ago.

On the other hand, two firms were remarkably different.

Vendor X’s salesperson fumbled the initial call because he was working at home and had a huge pipe break. So when his plumber arrived, he had to go. Not auspicious.

But he called me back and spoke more. He was eager to come in person for a demo, which he did. Then he called me a few times to discuss generally how I personally would benefit from getting the implementation right. He offered guidance on how to work with Marketing Automation and how to time the implementation for maximum effect. When I made it clear that we were on a limited budget until next April, he helped me understand how I could meet my internal needs using his service and adjusting the timing of certain things.

He also offered to have his CMO speak with my CMO, and his CTO sent me a signed book on using Marketing Automation.

In other words, he seemed to care about educating me and making sure I was comfortable with their firm. He was on the short list before he even returned my RFP questionnaire.

The second company was different. I wasn’t sure I liked their name. I wasn’t sure I liked what I saw on the first pass. I thought they had ignored an earlier request for information. But their name came up in a conversation, so I called them again and was SQLd! By the end of the day, I had a real sales person on the phone, although I was disappointed it took the entire day. He sounded eager to please. I asked him for more details, for a demo, and to fill out my RFP.

He was also, however, clear with me that his time that week was limited and that I was asking a lot of him. But he never said No to me. I had a demo the next day and the details by the end of the week. He showed me tools that were lacking in other services, but were included with his system.

So he moved closer to my short list simply because he sounded like he wanted to make it happen.

What is the lesson from this?

It is that the most responsive sales people will get the business or get closer to the money than someone who ignores the buyer.

Business and Pricing Model

One area where buyers, especially in Marketing, get upset is pricing. Buyers are upset not with the price, but what they thought was included with the price. Understand the pricing model of your vendors before you sign a contract!

It is amusing that many marketers don’t explore this enough because it is often our job to build pricing models and explain them to Sales and to our prospects.

Always ask up front, and early, “What’s your pricing model look like?”

We all know salespeople are reluctant to talk about price on the first call. Do not be afraid to bring it up early because you don’t want to waste time with vendors who:

  • Refuse to talk price.
  • Have confusing or unfair pricing models.
  • Are so outside your budget that no amount of “value” will ever make the deal happen.

Remember that there are solutions for all budget levels and your Needs Assessment should tell you what type of vendor you will evaluate to the call list. For example, if you run small roadshows of 50 people where there aren’t paid tickets, and you just need XYZ features, you will find some nice solutions out there at a fairly low price point. But if you actually want to run an entire User Conference with Booths, Exhibitors, Speakers, etc…there are enterprise level solutions that solve all that at a totally different price point.

One reason I chose Marketo originally was they made it clear they would grow their product with us as our ability to use it grew.

Some vendors price in a way that may not work for the way you want to work. Perhaps your budget is limited and you need to know the price won’t change as you use it. Perhaps you are growing fast and want to be charged in a clear way, but are happy to pay more as you grow. If your vendor cannot fit into your pricing needs, you may not want to go with them.

Pricing Model considerations:

  • All inclusive monthly fees.
  • Add Ons – what’s really included?
  • Pay per Unit
  • Minimum Fees
  • Annual payment discounts
  • Cancellation ability

Next time we’ll talk more about vendor pricing options and why some vendors don’t get it.

Filed Under: Marketing Technology

Reply Email Mining with LeadGnome

March 6, 2018 By Josh Hill

Today I had a chance to chat with Matt Benati, CEO and Co-Founder of LeadGnome. You may have seen some of Matt’s articles on how to use automated replies from customers and prospects to keep your database up to date, and find hidden opportunities. I wanted to learn more about Matt’s perspective on this topic as well as more about his product.

Josh: Tell us about the burgeoning world of Reply Email Mining.

Matt: Most marketing teams use Marketing Automation Platforms (MAPs) like Marketo to automate as much of their marketing processes as possible. Automating the process of sending emails to prospects and customers is a large part of this. MAPs focus on segmentation of databases, allowing for personalization and workflows that are triggered when a lead completes a specified action, such as downloading an ebook, watching a video, or even visiting certain pages of a site. For example, if someone downloads ABC, then automatically send XYZ follow-up email.

What is left out of the automation process is anything to do with the post-send of an email. Links, opens, clicks and other engagement with emails can be tracked — but the replies are typically not dealt with. Or, not dealt with efficiently. Hard and soft bounces are managed because the MAP can capture and remove bad emails from lists automatically. But auto-responses like Out-Of-Office and Left-The-Company, and even human replies like manual unsubscribe requests, are often ignored or deleted.  In fact, many folks have historically considered these reply emails a nuisance. Even MailChimp by default automatically suppresses Out-Of-Office responses from email threads.

It turns out, however, that the info within those replies provides significant intelligence and insight for sales and marketing teams. Many of us, myself included, have known about these hidden gems and have manually gone in and hunted and pecked the data for years. Now, as email mining is getting the attention it deserves, I am hearing over and over again, “I’ve been looking for this type of solution for years.” There is pent up demand for this critically strategic capability. This is not simply a tactical capability — it’s a must-have. Why? Because it provides significant advantages when we talk about driving revenue.

Josh: How did you get your firm started? Email reply data seems complicated.

Matt: It’s said that necessity is the mother of invention, and this is certainly the case for LeadGnome. Several years ago, in my first head of marketing job, my team and I were on the hook to deliver high-quality leads to the sales team. We used inbound, outbound, and nurturing methods, and all of these techniques had an email component.

My team had recently purchased a targeted list of contacts for an outbound campaign. I wanted to see how good the list was, so I began combing through the campaign response emails for bounces. I figured if the bounce rate was high, I’d ask the list vendor for additional contacts or a discount. However, as I scrolled through the response emails, I noticed something that immediately stopped me from counting bounces. I discovered gold buried in that mountain of emails – specifically I found leads in the body of out-of-office emails.

Wanting to make the most of my budget, I asked a marketing associate to plow through the out-of-office emails and mine the leads. His progress was slow and error prone as he performed the following process:

  • Open each email
  • Read the email searching for other contacts
  • Record this information (hand type or cut ‘n paste) into a spreadsheet
  • Import that information into our CRM system, Salesforce

Clearly, this was not going to scale. I figured there must be an automated email reply mining solution out there, so I searched the web. To my amazement, no solution existed. With a background in analytics, including data mining, I set out to develop an automated solution. The thing is, most of the valuable data in a reply email is in the body – in techno-speak, we call this the “unstructured data.” It requires advanced technologies, including the use of artificial intelligence, to effectively recognize and mine the relevant information from the unstructured data of an email. True reply email mining, like what LeadGnome does, goes far beyond signature scraping technology, to deliver more than just a phone number or title; the rich intelligence mined by LeadGnome directly translates to revenue opportunities.

Josh: LeadGnome sells the idea of high value leads from mining reply data. My experience is that I wanted to stop reviewing thousands of replies before I cared about new records. Why do companies seek you out? What’s that first conversation about?

Matt: It really depends on who I am speaking with and what their priorities are. In every case, the conversation starts with, “Please help; I can’t keep up with the volume of replies!” Then I start talking about what they want to accomplish with email mining – aside from automating the process. Here’s how their priorities typically shake out:

Marketing Operations Professionals:

  1. Database health/Compliance
  2. Enrich existing contacts
  3. New leads

Demand Generation Professionals:

  1. New leads
  2. Enrich existing contacts
  3. Trigger events

Sales Professionals:

  1. New leads
  2. Trigger events

Here’s what I’m talking about with these priorities:

Database health/Compliance – Database health is certainly an important need of our customers, especially considering that B2B data decays at a rate of about 70% annually. Clean data ensures you can reach prospects, helps with email delivery and sender reputation, and ensures you have accurate data to stay compliant with existing email spam laws (like CAN-SPAM and CASL). And with GDPR going into effect May 25, 2018, many organizations need solutions in place that can meet these stricter rules. We proactively built the LeadGnome platform to help ensure GDPR compliance and am happy to discuss details.

Enrich existing leads – Email mining maintains and enriches 72% of existing records annually by sending just 3 emails per month. Phone numbers, titles, email addresses, and other insight about your leads are mined and can be used to segment lists and personalize messaging.

New Leads – According to Gartner research, today’s B2B buying decisions now require an average of 7 people within an organization, so discovering new leads in target accounts is a top priority for both sales and marketing. Email mining generates pipeline by adding 20%+ net new contacts annually.

Trigger Events – A trigger event, or a significant change with a lead or account, represents a sales opportunity. It goes beyond delivering a lead, often bypassing parts of the sales funnel, to allow sales to leverage top line revenue opportunities. Most importantly, when certain trigger events are discovered via email mining, sales teams have a 6-12 month timing advantage over competitors and significantly increase their win rates.

While these benefits are reason enough for most marketing and sales professionals to want to add email mining to their toolbox, the ROI is the icing on the cake. Most LeadGnome customers realize an ROI of more than 600% in their first year. How? Automation reduces both hard costs (time/effort of manual process) and opportunity costs (redeploying resources to more appropriate tasks). When you add in the net new contacts (pipeline growth), and trigger events (found revenue opportunities), many customers realize a higher ROI.

Josh: Email use rules are tightening. What is the best follow up campaign for a new name obtained from Email Reply Mining?

Matt: LeadGnome has been leading the charge when it comes to privacy and privacy law discussions centering on mining reply emails. It turns out that net new contacts identified via auto-responses and human responses can be used lawfully under CAN-SPAM, CASL, and GDPR. If your readers have questions about using reply information lawfully, I’m happy to discuss it further. Of course, each company should consult their legal counsel for advice. [ed: no legal advice is provided in this article]

Regardless of whether you’re mining emails or not, you MUST have a process in place for being in compliance with these laws. To stay on the right side of all regulations, I recommend permission-based marketing. What has always been the best practice has even more significance in today’s highly-regulated world; specifically, the fundamental tenets of permission marketing. That is, when you reach out, be transparent with how you learned about the new contact. Transparency has always been the hallmark of permission-based marketing, and obtaining express consent from the get go is the surest way to remain compliant, especially with the upcoming GDPR changes, which are shaping up to be the strictest of all email spam laws.

Josh: I completely agree that following the principles of Permission Marketing is always the way to go and will enhance a company’s reputation online and off.

Josh: Where do your customers tend to make mistakes with LeadGnome? What’s stopping them from realizing its full potential? 

Matt: My philosophy is that customers continue using MAPs (like Marketo) that they know and love. I want our customers to use the systems they use daily and I believe that they shouldn’t have to learn a new workflow system presented by a company like LeadGnome.

The challenge with that, however, is they need to create the MAP programs to automate the business logic/workflows that make sense for them. For example, some might alert sales reps via email; some via text. Because all companies do things differently, I really felt strongly that the best place to create these workflows is within your MAP. For example, your workflows may combine reply email mining result data with other data stored in your MAP – this is done most efficiently within the MAP itself.

Josh: Why do you think the major MAPs have left reply management out of their core product?

MAPs have been in place for many years, but the technology needed to mine the unstructured data from reply emails simply has not been there. Artificial Intelligence technology is how LeadGnome mines emails, but it has only become feasible and more accessible in recent years. MAPs have historically focused on the sales and marketing processes leading up to and including sending emails, but as mentioned before, the post-send process has remained largely untouched.

LeadGnome complements your MAP by filling this automation gap, closing the loop on the email marketing process and leveraging a previously untapped data source.

Josh: What percentage of each email send yields some sort of reply?

From analyzing real LeadGnome customers’ email campaigns, I have found that 2% to 3% of email send volume produces replies. Of those replies, 50% to 60% generate alternate contacts (net new contacts).

Josh: Since we both care about Permission based marketing, what are the ethics in using data obtained this way?

Matt: In a B2B world, your existing contacts or the company you are interacting with is asking you to engage with others within the organization when they put auto-responses like Out-Of-Office and Left-The-Company in place.

In an OOO, there is usually an alternate person to contact while your original contact is out of the office. Same with a Left The Company reply, as there is usually a replacement contact included in the auto-response. Because your contact gave this information freely, you are legally able to reach out to the new contact. As I discussed earlier, however, it’s always a good idea to practice permission-based marketing, reach out and be transparent in how you received the new contact’s information, and ask for them to opt-in to receive communication from you. In fact, for GDPR, it is a requirement of the “legitimate interest” rule, to provide specific information when communicating with these new contacts.

Josh: I see two groups of Reply Email tools: reply mining apps and reply conversation Bots with “AI”. Do you see the reply mining sector heading more toward AI reply bots like Conversica? 

Matt: I think there is certainly a place for bots that reply to conversations for their human counterparts. This could be an expedient solution for high-volume or “pat answer” situations. However, we live in a world where people want more personalized engagement with real people. I speak a lot about account-based models, where personalization is reaching new levels because the people we want to engage with demand it. So realistically, I don’t think that bots can replace humans.

I tend to subscribe more to paradigms like Jill Konrath’s Intelligence Conversations model. We owe it to our customers to learn as much as possible about them and then earnestly engage — human to human — to build value-based rapports. Reply Email Mining provides much of the information needed to start and continue these conversations.


Matt, thank you for sharing your perspective today. Email reply management is a natural win for automation and I believe every MOPS professional should have this in her arsenal.

Filed Under: Marketing Technology

Dealing with Duplicates in Marketing Automation

February 15, 2018 By Josh Hill

Remove Duplicates

One of the great features of marketing automation platforms (MAPs) is the ability to automate deduping. Most MAPs look at Email Address as the unique identifier. While this doesn’t stop all dupes, it does take care of 80% of new dupes from imports, form fill outs, and events.

But you will still have duplicates from Sales, CRM history, and people filling in different information. So how can you get closer to zero dupes?

How Marketo handles duplicates

Marketo automatically dedupes leads based on email address. The dedupe works only when you enter new leads into Marketo from:

  • List Import
  • Marketo Form (iFrame or Marketo Page is ok)
  • Direct creation in Marketo database.
  • Direct creation through API. (exceptions apply)

Thus you should do your best to create new leads using the above methods. I can’t speak for other systems, but they are probably similar in approach. There are some caveats to Marketo’s approach:

  • Records from the CRM will never be deduped. Your Sales team can create dupes!
  • Existing Records on the first sync will also not be deduped. This is why you should clean up your database before implementation.
  • If there are Duplicates by Email Address, Marketo will choose the most recently updated Record to append to. This may not be the record you actually want.

In Marketo and your CRM, you can merge records manually, but not automatically.

Choosing the Right Record in Marketo

The use case here is that you may have a Customer Record that was selected to receive an important billing message. You want that Record to be tagged as having Sent the email to.

When duplicates exist in Marketo, you will upload a static list in CSV with one column: email address. But Marketo cannot guarantee it will select the exact Record you saw in your CRM. So if it chooses a loose SFDC Lead instead, your system will record the Email Send, but it won’t be obvious to anyone looking at the Customer’s main CRM record.

marketo-dedupe-sheet

Most of the time this is not a big deal, but it can be a big deal when you want to record billing or legal messages have been sent. You can be sure that a Customer will call up sales to complain about a price increase they never saw. When Sales looks at the Contact, no email is shown. But when you look across all records, you can prove the email was sent. As a MOPS pro, you can be sure this scenario will occur and that the salesperson won’t always check possible dupes.

To solve this, you would need to do one of two things:

  • Option 1: use SFDC Report to Add to SFDC Campaign and then point Marketo at that correct list. This won’t always work if you use SFDC Campaign as attribution tools.
  • Option 2: use a CRM flag to identify the specific record to Marketo. It’s ok, but not scalable.
  • Option 3: use Talend (or similar tool) to map the SFDC ID Record against the Marketo ID Record to Add to List.
  • Option 4: paste a list of SFDC IDs into the SFDC ID filter in a Smart List.
    • Option 4 is only possible if you have less than 2499 rows to place in the filter. I don’t like this option because it’s not scalable.

In an ideal world, Marketo would enable a List Import option to map against better unique database keys like SFDC ID. Until that happens, those are your options.

But this case is not unique to Marketo — all MAPs that rely on email address deduping will encounter this scenario with a CRM or another database.

Why Duplicates Matter to You

Every record in your database costs you money and time in some way. A single record may be a fraction of a cent in some databases. In most MAPs that charge by the record, you are charged whether or not that record has value to you. Per record fees may be $.05 to $.20! That matters because, in my experience, most B2B marketing databases have about 18% useful prospect records and perhaps 60% bad or inactive records that just sit there. If you have 100,000 records, that’s $12,000 per year in deadweight. The rule of thumb bandied about is 25% of your database goes bad every year.

  • Clutter – not being able to get accurate counts for segmentations.
  • Compounding Bad Data with Sales – salespeople update the wrong records and chaos ensues
  • Spam Law Compliance – issues with duplicates not having the right permissions could end up as a nasty letter or legal action.
  • Vendor Costs – most vendors use the number of records as a pricing scale, even if you have duplicates. Managing this is your problem, not the vendor.
  • Email Costs – if you use a vendor that prices per email, then you will definitely have an increased cost.
  • Inaccurate reports – incorrect records invariably lead to questionable reports and bad decisions.
  • Double Purchases: bad data quality and dupes often means Salespeople (and you) will buy lists that have the same people.

There are tons of studies by data vendors that make the case even more clearly. A 2011 Gartner study suggested poor data quality lowered productivity 20%. And SiriusDecisions (and data processing vendors) have shown how bad data compounds over time.

Hunting Down Sources and Preventing Dupes

You can prevent duplicates. One way is to map out how data enters your systems and develop processes for deciding which systems can create records or find and append records. The steps I would take include the following:

Map of All Data Entry Methods:

  • Create in CRM
  • Import into CRM
  • Product database
  • List Import into your MAP
  • Salespeople/Manual Creation
  • Lead fills out a form

Then decide which sources are permitted and who is permitted to create records.

  • Which system is the Source of Truth that trumps other sources?
  • Which records will win during a merge?

Those people and systems then need a process to ensure they attempt to identify dupes and handle them. You can create a hierarchy of record scenarios to build automation rules.

If you are looking for specific rules over which fields and records to choose to override, you can think about some of the options:

  • Prefer Older Record over newer.
  • Prefer more complete record to less complete.
  • Prefer the Source of Truth Record against an incoming record.
  • Choose the existing data rather than the purchased data (if not empty).
  • Choose the Customer record over the Lead record.
  • Choose the business email record over the matched Gmail record.
  • Choose the data from Data Vendor 1 over Data Vendor 2.
  • Choose the most recently updated field over the older field.
  • Average the scores (although Marketo adds them).
  • Use the score of the more recent lead.
  • Choose the record that is furthest down the funnel.

Blocking Dupe Creation

  • Using a CRM Tool like Dupeblocker: enforce a search of the database before creation.
  • Using Automation to use unique keys across systems to match up before creation.
  • Using Email Address deduplication in your MAP.
  • Block Salespeople from record creation.
  • End use of SFDC Leads and only use Account-Contacts. (Much harder!).
  • Sync your CRM-MAP with all records. Not syncing all records ensures dupe creation.

At some point, you will have to accept that duplicates will exist and have a tolerable threshold. My personal rule of thumb is that you are doing very well if 3% of your database are dupes by email address. Duplicates by Name or other fuzzy criteria may be slightly higher, so you will need more powerful tools to identify that count. I have often come across duplicates where the company had multiple domains and Company Names, which would be very difficult to fully identify without knowing their particular case.

At the end of the day, your team must decide how much bad data is costing you against the cost of setting up an automated process to clean the database. For smaller databases, some simple rules will be enough with your email address deduping. For databases over 1MM records, I personally recommend an automated solution. The earlier you can do this, the less frustration you will have in the future.

Image Credit: barbourians

Filed Under: Marketing Technology

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