The idea of too many leads is a dream for most sales and marketing teams. But if your team can’t laser-focus on your optimal audience to drive conversion in your pipeline, that dream quickly turns to a nightmare.
In this deck, you'll learn:
1. What are Predictive Analytics?
2. How can you benefit from Predictive Marketing?
• Define the buyer
• Understand the actions that lead to purchase/win
• Replicate: Rinse, repeat
3. What are the simple next steps to get started?
Almost every marketer we talk with feels like they have one of two problems -- they either have too many leads or not enough.
If they have low lead volume or already follow-up on every single lead, the focus is on how to build more pipeline.
If they have too many leads, their main challenge is prioritization. Many organizations struggle to find out how to categorize and become more efficient with limited resources.
While predictive marketing can help with both challenges it is broadly applicable throughout the pipeline, regardless of the initial problem it helps solve. More often than not, if a company has too many leads, they will always want more. It s a great problem to have, but again, an efficient qualitative approach to addressing it is key.
Prioritizing and identification of the highest value opportunities with a high propensity to buy can make you a hero to sales.
So what is Predictive Marketing? Ultimately, it can be boiled down to a fairly simple concept. Use your historical internal data combined with the universe of external data to predict who your next customer should be.
The value of Predictive Marketing starts with Audience Selection, which is the process of not only understanding your model or best fit customer, but ultimately looking at every potential customer in your market to choose your audience. Predictive Marketing enables you to have a point of view one every single potential account in your market, and we then help you prioritize and select your optimal audience.
This is a critical concept and is the baseline for Predictive Marketing. At EverString, our entire focus is driven by this single concept. We hire the best data scientists and collect and curate massive amounts of data in order to make sure that your models and ultimately, the accounts and leads we deliver to you are the best in the business. This is our singular focus.
LeadMD Overview –
Top tiered Marketo Preferred Partner
Why we specialize in Marketo
2500 + engagements
Early adopters – started out as a marketing automation agency NOT as a digital marketing agency.
30 + Certified experts
Issues with Data we can see:
Marketers base models off data they know is crap
Behavioral data often simply indicates good content
Deconstructed data is subjective
The best data comes from conversations with people in the know
CRM data is degrading the moment we enter it
CRM is like Jazz
[VINCENT}
Demographic: Company Fit Score
Behavioral : Engagement
Psych: Intent
We must look at multiple dimensions to get a true picture. Most PLS vendors only look at one dimensions
----- Meeting Notes (3/20/15 16:23) -----
Fit Score
Engagement Score
Intent Score
Right Message, right time, right fit
Traditional marketers are looking to scale system but marketers are only using the tool to do more of the same – not to scale segmentation and better messages
This is the proof of the entire hypothesis – traditional lead scoring doesn't’t work, because it’s far to one dimensional.
This proves that predictive modeling is not a graduation point – it is the only reliable way to “score” leads and customers
Let’s take a look at some of the indicators
Most common ask here is “give us a list’ – even we asked that
They make no sense on their own
It’s about the relationship of data points, not the points themselves
If someone is in Rhode Island does not make them a great buyer
If someone is in Rhode Island, who has Marketo, who has a good Marketing spend, who was on our pricing page in the last 30 days and has signed up for our best practices series who JUST searched for marketing automation consultants – THAT’S the hidden treasure.
Let’s take a look at some of the indicators
Most common ask here is “give us a list’ – even we asked that
They make no sense on their own
It’s about the relationship of data points, not the points themselves
If someone is in Rhode Island does not make them a great buyer
If someone is in Rhode Island, who has Marketo, who has a good Marketing spend, who was on our pricing page in the last 30 days and has signed up for our best practices series who JUST searched for marketing automation consultants – THAT’S the hidden treasure.
Color the inner circles in
Label the Account Personas as such
Surrounded by a buying committee
Do you have the entire icp in your database? 55% coverage 100 %
What’s an ideal buyer persona
What’s the differences in
Two dimensions, the individual, who they are, what level they are at, what their role is, the distance from purchasing power
How much autonomy to make that decision, if they have to bring in that many people.
it, the distance in buying power?
Doesn’t align to industry
The person and their distance to purchasing power
We will do a run down here on the results. It will remain high level.
If the buyer works like this, what do you do?
Gallery, in sales insight, new piece of content, everyone
If the buyer works like this, what do you do?
Gallery, in sales insight, new piece of content, everyone
Discuss what we are testing now.
Products aligned to personas
Sales teams assigned via persona
Consultants assigned
Tailored Sales plays
Persona based nurture through MKTO persona assignement
Post opp survey