Sales and Marketing Automation: Explaining the Difference

Is the difference between sales and marketing automation confusing you? There’s a reason why. Sales teams are being pushed to hit prospecting “activities” numbers — to the exclusion of making those activities count.

Is the difference between sales and marketing automation confusing you? There’s a reason why. Sales teams are being pushed to hit prospecting “activities” numbers — to the exclusion of making those activities count.

As one of my students selling enterprise software put it, “I’m glad to send out X number of emails per week and leave Y number of voicemails … so long as most of those touches bring me closer to a meeting. I’m not willing to hit my numbers for the sake of hitting my numbers — and that’s what management is demanding.”

Here’s the rub. “Mass marketing” mentality is creeping into most sales departments — especially SDRs and BDRs (sales and business development reps).

The result is a blurring between sales and marketing, broadly. But also a blurring between sales and marketing automation tools and how they’re being applied. Inside sales teams are behaving like mass marketing agents. Worse, field reps selling into enterprise accounts are being forced to pump out templated emails to C-suite and officer level prospects.

And it ain’t workin’.

Is Sales a Numbers Game?

Remember the old adage, “Sales is a numbers game?” Given LinkedIn, social media, email, postal mail, cold calling, etc., we need a new name; a more scientific name. They call it “Activity Based Selling.”

Followers of Activity Based Selling (ABS) believe, “sales is a numbers game — won primarily by those who knock on more doors.”

But here’s where it gets ugly. Sales is (and always will be) a numbers game. Is business growth purely quantitative? Certainly not. But proponents of ABS are excluding quality of conversation from sellers’ strategies. Many organizations are over-focusing on reps hitting activity quotas — neglecting the qualitative communication skills needed to approach C-level decision-makers.

In theory ABS makes good sense. In practice it turns out to be spammy, dangerous and ineffective.

Marketing Automation Isn’t Sales Automation

It may sound stupid to say marketing automation isn’t sales automation. Truth is, you may agree in theory: Marketing is distinct from sales. But in practice are your sellers behaving like mass marketers when using email, voicemail and social?

This is where things get cloudy.

According to sales automation software provider Outreach.io, marketing automation is not a substitute for a sales engagement platform. Well, duh. But interestingly, this software vendor prefers the word “engagement” over “automation,” with good reason. Folks in charge of purchasing these tools often don’t see the difference — based on how they intend to use marketing and sales automation tools.

When you intend on using both to send “campaigns,” look out!

Both sales and marketing automation tools have the capability to send en mass. I’m convinced this is because sales automation companies would go broke otherwise.

Everyone demands sellers to send mass emailed campaigns. Big mistake.

Outreach.io rightly advises marketing automation:

  • is ideal for generating leads, but not working them;
  • is too technical and feature-heavy to onboard new reps quickly;
  • lacks flexibility needed for personal conversations;
  • doesn’t enable reps to make calls and interact on social media;
  • send emails via third party servers, not a rep’s inbox, which increases chances of getting caught in spam filters

So What’s the Difference?

The difference is simple in theory and what should be practiced: One-to-many (marketing) message management and one-to-one (sales) message management. It’s the difference between trying to earn whitepaper downloads and webinar registrants, and earning the right to converse with a client and qualify their need.

Marketing automation should be generating leads via mass marketing. Sales engagement (automation) tools should be helping sellers to do what they do best — help those leads qualify or dis-qualify themselves as customers.

Can you do this using cut-and-paste templates you found on Google?

Heck no.

Today’s most effective sales reps — on inside or in field — use qualitative, one-on-one conversations. Email plays a vital role in starting and moving conversations toward closure. Problem is, many who invest in sales automation software use it to push static, impersonal templates that scream, “delete me!” to prospects.

Prospecting templates don’t work.

The Problem With Activity Based Selling

Proponents of ABS tend to believe “If we focus on what sellers can control (activities) … and not the outcome we desire (customers buying) … sellers will perform better.” Thus, management focus sellers on “activities” that encourage a conversation via:

  • reach
  • persistence
  • education

Trouble is, those ideas easily morph into pushing information at prospects (low skill). Instead, C-level buyers demand sellers find ways to earn discussions by attracting (pulling) them into a qualitative, early-need-stage dialogue.

Worse, demand generation and sales enablement teams supporting reps instruct them to not focus on the sale. While pushing for the sale is not appropriate, telling a sales rep “don’t focus on selling” forces reps to ask, “what should I do then?”

Too often the answer is found in marketing-speak. Reps resort to pushing email messages at clients about features, benefits, solutions and webinars. Instead, effective reps provoke replies using non-marketing-speak messages based on problem-solving and other sensitive issues they’ve managed to research.

Thus, ABS demands reps to perform many touches (activities). The nature of what ends up being pushed out is purely quantitative marketing noise aimed at educating clients who have not yet asked to be educated!

Stop Sending Templates

At best, even when sellers are not pushing out education-oriented mass messages, they are sending out drivel like this…

Hi Sam,
I wanted to reach out because my company [insert vendor name] helps organizations like [target company name] [top 10 list of pain/value propositions every vendor claims — e.g., increase productivity, reduce sales cycle time, boost engagement, manage leads etc.]

Our solutions have helped customers like [list of generic famous companies designed to impress reader] see an improvement of [insert ROI stat].

Do you have 15 minutes to speak this week? Looking forward to hearing from you!

Templates don’t work nor do premature meeting requests. Effective sellers use templates to customize messages faster, not send faster. They use sales automation and engagement tools to start and qualify one-to-one conversations using qualitative (yes, time consuming) tactics designed to earn them.

Research is a key element of effective cold email messages — proving you’ve done homework on prospects multiplies response rates.

Add in a Qualitative Element

Provoking conversations with C-level executives is possible. It isn’t “cut-and-paste-easy.” Nor is pushing educational or value-added messages at them (before they’ve requested it) going to work. What does work is relatively simple: It mostly involves trimming back all messages to two to four sentences. Literally.

The other key element is sparking curiosity in cold messages.

True: It’s best to focus on what you can control (activities) … and not the outcome you desire (customers buying). But the answer is not a purely quantitative strategy—especially when calling into the C-suite.

Standardized templates do not work. They feel too “mass mailed.” Easy to spot, instant delete.

But a mental-triggers-based approach to message design—that can be very repeatable — does.

Customization is key. Psychology is front-and-center to triggering response.

What is your experience lately?

A Popular (yet Ineffective) LinkedIn Tactic

Considering investing in LinkedIn automation software? Already using automated tactics? Beware: Automation is not helping social sellers start conversations. Don’t let your hopes or a LinkedIn “expert” (charlatan) tell you otherwise. This isn’t my opinion. I speak from experience — and that of my customers.

LinkedIn logoConsidering investing in LinkedIn automation software? Already using automated tactics? Beware: Automation is not helping social sellers start conversations.

Don’t let your hopes or a LinkedIn “expert” (charlatan) tell you otherwise.

This isn’t my opinion. I speak from experience — and that of my customers.

I don’t like to speak in absolutes. Nothing is certain in our world. But automating the gathering of lead data and sending messages to prospects wastes time, damages reputation and what’s worst is buyers see through it — instantly.

It’s spammy.

Also, LinkedIn is cracking down and suing service providers. It took a while but Microsoft has had enough.

Short-cuts rarely work in life. Buckle-down and do the work. And yes, I know you need to scale. Me too. Tech tools like LinkedIn help us scale time. But LinkedIn automation is ineffective.

Lately, it can also hurt you.

Automating Outreach and Scraping Contact Data

We need targets to call on: Companies, decision-makers and contact data. LinkedIn is a database. But gathering contact data is time-consuming. Plus, getting these contacts to connect with us (open the door to communication) takes time and effort.

Wouldn’t it be great to automate the data collection, connections and messaging? We could mass email messages to prospects — without much effort. We’ll reply to the responses, manage the leads.

Enter LinkedIn automation tools.

But beware of reality:

  1. Automated profile viewers and contact data scrapers are being sued by LinkedIn/Microsoft;
  2. Non-personalized (spammy) or “personalized” (fake personalization) messages aren’t helping sellers start conversations with buyers;
  3. Decision-makers are actually hiding from overzealous sellers and accepting fewer connection requests.

How Automation Software Works

You look up a group of contacts using a LinkedIn search. Boom. Software automatically:

  • Grabs those search results
  • Views each contact’s profile
  • Scrapes the screen (cuts-and-pastes name, company, title, etc. into a spreadsheet)

Software will also:

  • View profiles
  • Invite people with keywords or titles to connect
  • Automatically send them welcome messages when they accept
  • Automatically endorse them
  • Automatically send them congratulatory messages when they have a birthday, work anniversary or change jobs
  • Automatically send sales messages to large swaths of your connections

Sounds great. But let’s pretend you are Microsoft (LinkedIn’s new owner).

You just paid $26 billion for this data. How do you feel about people scraping it? How do you feel about automating all of these non-personalized functions (which are all trying to look personalized and social)?

That’s why LinkedIn is suing these service providers.

Automation tools are popular. But these are often “companies” that have no public contact data themselves! Companies that, in fact, aren’t companies … and have (for years now) operated in clear violation of LinkedIn’s Terms & Conditions.

LinkedIn prospecting expert, Bruce Johnston, is blunt:

“It is instructive that I went through my list and less than half of the companies I added 12 to 15 months ago still exist.”

Election Polls and the Price of Being Wrong 

The thing about predictive analytics is that the quality of a prediction is eventually exposed — clearly cut as right or wrong. There are casually incorrect outcomes, like a weather report failing to accurately declare at what time the rain will start, and then there are total shockers, like the outcome of the 2016 presidential election.

screen-shot-2016-11-17-at-1-03-34-pmThe thing about predictive analytics is that the quality of a prediction is eventually exposed — clearly cut as right or wrong. There are casually incorrect outcomes, like a weather report failing to accurately declare the time it will start raining, and then there are total shockers, like the outcome of the 2016 presidential election.

In my opinion, the biggest losers in this election cycle are pollsters, analysts, statisticians and, most of all, so-called pundits.

I am saying this from a concerned analyst’s point of view. We are talking about colossal and utter failure of prediction on every level here. Except for one or two publications, practically every source missed the mark by more than a mile — not just a couple points off here and there. Even the ones who achieved “guru” status by predicting the 2012 election outcome perfectly called for the wrong winner this time, boldly posting a confidence level of more than 70 percent just a few days before the election.

What Went Wrong? 

The losing party, pollsters and analysts must be in the middle of some deep soul-searching now. In all fairness, let’s keep in mind that no prediction can overcome serious sampling errors and data collection problems. Especially when we deal with sparsely populated areas, where the winner was decisively determined in the end, we must be really careful with the raw numbers of respondents, as errors easily get magnified by incomplete data.

Some of us saw that type of over- or under-projection when the Census Bureau cut the sampling size for budgetary reasons during the last survey cycle. For example, in a sparsely populated area, a few migrants from Asia may affect simple projections like “percent Asians” rather drastically. In large cities, conversely, the size of such errors are generally within more manageable ranges, thanks to large sample sizes.

Then there are human inconsistency elements that many pundits are talking about. Basically everyone got so sick of all of these survey calls about the election, many started to ignore them completely. I think pollsters must learn that at times, less is more. I don’t even live in a swing state, and I started to hang up on unknown callers long before Election Day. Can you imagine what the folks in swing states must have gone through?

Many are also claiming that respondents were not honest about how they were going to vote. But if that were the case, there are other techniques that surveyors and analysts could have used to project the answer based on “indirect” questions. Instead of simply asking “Whom are you voting for?”, how about asking what their major concerns were? Combined with modeling techniques, a few innocuous probing questions regarding specific issues — such as environment, gun control, immigration, foreign policy, entitlement programs, etc. — could have led us to much more accurate predictions, reducing the shock factor.

In the middle of all this, I’ve read that artificial intelligence without any human intervention predicted the election outcome correctly, by using abundant data coming out of social media. That means machines are already outperforming human analysts. It helps that machines have no opinions or feelings about the outcome one way or another.

Dystopian Future?

Maybe machine learning will start replacing human analysts and other decision-making professions sooner than expected. That means a disenfranchised population will grow even further, dipping into highly educated demographics. The future, regardless of politics, doesn’t look all that bright for the human collective, if that trend continues.

In the predictive business, there is a price to pay for being wrong. Maybe that is why in some countries, there are complete bans on posting poll numbers and result projections days — sometimes weeks — before the election. Sometimes observation and prediction change behaviors of human subjects, as anthropologists have been documenting for years.