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Sorting Through the Scoring Mess - SiriusDecisions

Sorting Through the Scoring Mess - SiriusDecisions | The MarTech Digest | Scoop.it

Given the variety of options for both the model (approach) and the technology to support scoring, we felt it was important to identify and define the options. From our observations, today’s perspective and guidance is focuses too heavily on the technology (e.g. marketing automation vs. predictive), without a broader consideration for what approach makes the most sense for an organization. The types of scoring models include:

  1. Manual. Cherry-picking; no standardized methodology or process – not a recommended approach.
  2. Assumption-driven, rules-based. Attributes and weighting developed according to assumptions vs. informed by data – not a recommended approach.
  3. Data-driven, rules-based. Uses statistics to identify and prioritize attributes and behaviors that are configured into the model. When the scoring threshold is reached, the prospect is handed off for followup – a recommended approach.
  4. Predictive prospect prioritization. Prioritization models work like lookalike models – they mathematically compare known prospects and accounts to an ideal and prioritize accordingly. Followup is determined by statistical processes.
  5. Hybrid. Combines data-driven, rules-based and predictive prospect prioritization to determine hand-off and prioritize followup. Hybrid approaches score the account via predictive and deliver the contact via marketing automation platform (MAP) behavior.
CYDigital/marteq.io's insight:

I've completed abandoned lead scoring as a viable tool.

 

RYZZ: it’s a better approach to MarTech for B2B Marketers.

 

#MarTech #DigitalMarketing

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What are the most used Marketing Automation techniques? - Smart Insights

What are the most used Marketing Automation techniques? - Smart Insights | The MarTech Digest | Scoop.it
Chart of the Day: Don't forget your Lead Scoring We all know about Email Marketing Automation, but what is Lead Scoring? In the chart, we can see that Emai. Marketing topic(s):Marketing automation. Advice by Kim Greenop-Gadsby.
CYDigital/marteq.io's insight:

Lead Scoring? Here's why: it doesn't tell you anything about specific products!

 

Monetize your excess MarTech with RYZZ. It’s a new approach to MarTech for B2B Marketers.

 

#MarTech #DigitalMarketing

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You Need to Define an Effective Criteria for Lead Scoring - Marketing Insider Group

You Need to Define an Effective Criteria for Lead Scoring - Marketing Insider Group | The MarTech Digest | Scoop.it
Lead scoring for B2B businesses doesn’t have to be a complicated process. For best results, follow these simple steps as you establish your lead scoring criteria:
  • Identify the criteria you should use. 
  • Define your target market. 
  • Determine your ideal lead. 
  • Track your customer behavior. 
CYDigital/marteq.io's insight:

It's not that difficult to do. It is VERY difficult to change it.

 

Visualize your Marketing Stack. marketingIO will analyze your marketing technology and deliver a visual of your MarTech Stack. Free. Go here: http://go.marketingio.com/stack_analysis 

 

marketingIO: MarTech for B2B Marketers. Strategy, Software, Services, Support, Staffing.  Go here to submit RFQs: http://www.marketingio.com #MarTech #DigitalMarketing

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Strategies for More Effective Lead Scoring - Chiefmarketer

Strategies for More Effective Lead Scoring - Chiefmarketer | The MarTech Digest | Scoop.it
Today, market-leading lead scoring solutions are using advanced machine learning and artificial intelligence algorithms that process thousands of columns of data, which can be assigned to basic contact details to deliver accurate scores that rank a lead’s propensity to convert.

Not all lead-scoring solutions are equal in their functionality and performance. For instance, many of these solutions rank buyers’ behavior based on basic actions such as downloads, website visits, form fills or geographic location, providing a glimpse into a given buyer’s motivations. Artificial intelligence technology takes a step further, providing marketers with predictions of a prospect’s behavior.
CYDigital/marteq.io's insight:

Visualize your Marketing Stack. marketingIO will analyze your marketing technology and deliver a visual of your MarTech Stack. Free. Go here.

 

marketingIO: MarTech for B2B Marketers. Strategy, Software, Services, Support, Staffing.  Go here to submit RFQs. #MarTech #DigitalMarketing

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6 Lead Scoring Techniques You Should Use With Marketing Automation - GetResponse Blog

6 Lead Scoring Techniques You Should Use With Marketing Automation - GetResponse Blog | The MarTech Digest | Scoop.it

"Technique 1. Increase lead score based on interactions.

Technique 2. Decrease lead score based on expressed interest level.

Technique 3. Increase lead score based on disclosed preferences.

Technique 4. Progressive profiling.

Technique 5. Lead grading based on profile fit.

Technique 6. Interactive content marketing."

CYDigital/marteq.io's insight:

marketingIO.com bridges the gap between your MarTech and your in-house experience. Contact us. #MarTech #DigitalMarketing

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What Are the Most Popular Lead Stages Used by B2B Enterprise Marketers? - MarketingCharts

What Are the Most Popular Lead Stages Used by B2B Enterprise Marketers? - MarketingCharts | The MarTech Digest | Scoop.it
CYDigital/marteq.io's insight:

Curated for you by marketingIO: One Source for All Marketing Technology Challenges. See our solutions.  #MarTech #DigitalMarketing

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Lead, Prioritize, Win: Moving To Predictive Prioritization - Radius

Lead, Prioritize, Win: Moving To Predictive Prioritization - Radius | The MarTech Digest | Scoop.it
Traditional lead scoring uses simplified models that require frequent manual updates. While that’s great for identifying bad leads, it’s not very good at identifying who is more likely to buy.

That’s where predictive scoring comes into play.

Predictive scores are far more accurate because they’re built to access large external datasets and use machine learning – making use of explicit and implicit signals you don’t have in your marketing automation (MAT).

With predictive prioritization, you can create an effective action plan, allowing sales to focus on the right opportunities and reach out to prospects most likely to buy.
CYDigital/marteq.io's insight:

Predictive: quickly moving from nice to have...

 

Email your comments to joe@marketingIO.com. I’ll publish it here. marketingIO: One Source for All Marketing Technology Challenges. See our solutions.  

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How to Get Lead Scoring Right the First Time - Marketing Insider Group

How to Get Lead Scoring Right the First Time - Marketing Insider Group | The MarTech Digest | Scoop.it
KEY QUESTIONS TO ANSWER BEFORE IMPLEMENTING LEAD SCORING
  • What are the score-able attributes captured?
  • Who owns the leads coring model?
  • How many scoring groups will we monitor?
  • What are the scoring actions we will take against these groups?
  • How will we validate and measure the scoring model?
  • How will we validate and measure the scoring models?
  • How should sales be alerted when a lead scores high?
  • Have marketing and sales agreed on all aspects of the model?
  • How should we display scoring data in CRM?
  • Should scores degrade over time due to lack of activity?
CYDigital/marteq.io's insight:

NEW: Experience Remarkable Planning Accuracy With New, FREE Growth Hacking Tool. Go here: http://goo.gl/UjcA8x 

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Introducing Multiple Scoring Categories - Pardot

Introducing Multiple Scoring Categories - Pardot | The MarTech Digest | Scoop.it
With Pardot, you’ve always had the ability to track prospect engagement with your brand by assigning points to every action a prospect might take and tracking overall engagement as a prospect score. But companies with multiple products or business units need the ability to track not just engagement with their brand, but engagement with each of their products or business units. With the introduction of Multiple Scoring Categories, marketers now have deep insights into what prospects are interested in so they can nurture them more effectively, pass them to the right rep at the right time, and identify the cross-sell and upsell opportunities that are most likely to convert.

Pardot’s new Multiple Scoring Categories feature allows you to track prospect engagement at the aggregate and individual product or business unit levels. Take for example Acme, a company that sells both Hammers and Mallets. When a prospect comes to the Acme website and downloads a white paper outlining the features of Acme’s new line of Hammers, an activity that is valued at 10 points in Acme’s scoring model, two things will happen. First, that prospect’s overall score will be raised by 10 points. Second, that prospect’s score for Hammers will go up by 10 points.
CYDigital/marteq.io's insight:

marketingIO: One Source for All Marketing Technology Challenges. See our solutions.  

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6 Ideas to Expand Your Lead Scoring Model Beyond the Basics - Oracle

6 Ideas to Expand Your Lead Scoring Model Beyond the Basics - Oracle | The MarTech Digest | Scoop.it

marketingIO: One Source for All Marketing Technology Challenges. See our solutions.

CYDigital/marteq.io's insight:

Easier said than done, as you need a MAP that can provide this capability and flexibility. Look to RightOn Interactive as a possibility.

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Traditional vs. Predictive Lead Scoring: What's the Difference? - HubSpot

Traditional vs. Predictive Lead Scoring: What's the Difference? - HubSpot | The MarTech Digest | Scoop.it

marketingIO’s Outsourcing delivers the vetted talent you need under your complete management and control. 

CYDigital/marteq.io's insight:

FYI...

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Lead Scoring 101: How to Use Data to Calculate a Basic Lead Score - HubSpot

Lead Scoring 101: How to Use Data to Calculate a Basic Lead Score - HubSpot | The MarTech Digest | Scoop.it

marketingIO bridges the gap between your MarTech and your in-house experience. 

CYDigital/marteq.io's insight:

Basics. 

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B2B Lead scoring infographic - Smart Insights

B2B Lead scoring infographic - Smart Insights | The MarTech Digest | Scoop.it

Dark marketing clouds ahead? Let us help you see clearly. Contact us.

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Lead Scoring Methodology - Smart Insights

Lead Scoring Methodology - Smart Insights | The MarTech Digest | Scoop.it

iNeoMarketing’s MarTech Managed Services solves numerous B2B Marketing challenges. Contact us to see how.

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Lead Scoring 101: How to Build a Hierarchy [Infographic] - Pardot

Lead Scoring 101: How to Build a Hierarchy [Infographic] - Pardot | The MarTech Digest | Scoop.it

iNeoMarketing.com bridges the gap between your MarTech and your in-house experience. Contact us.

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5 Best Practices for a Successful Lead Scoring Model - Pardot

5 Best Practices for a Successful Lead Scoring Model - Pardot | The MarTech Digest | Scoop.it

iNeoMarketing’s Outsourcing delivers the vetted talent you need under your complete management and control. Contact us to see how.

CYDigital/marteq.io's insight:

Especially #1. That's particularly pertinent when you consider the digital shelf life of a scored behavior.

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5 Steps to Creating a Successful Lead Scoring Program - Act-On

5 Steps to Creating a Successful Lead Scoring Program - Act-On | The MarTech Digest | Scoop.it

Predictive Analytics is the next step in Marketing Automation. Contact us to see how.

CYDigital/marteq.io's insight:

Another smart approach to scoring. Whatever you do, please don't fling numbers up against the wall to see what sticks. Get a methodology...and document it.

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Maximizing Lead Scoring & Analytics: How To Use Big Data In B2B - Marketing Land

Maximizing Lead Scoring & Analytics: How To Use Big Data In B2B - Marketing Land | The MarTech Digest | Scoop.it

► About Us: iNeoMarketing provides Marketing Technology services, applications and support to B2B companies who do not have the required resources, knowledge or expertise. Visit us at ineomarketing.com. ◄

CYDigital/marteq.io's insight:

You probably don't have big data, and you really don't need it. So long as you have a good MAP implemented, you can take advantage of all these benefits. It just requires a bit of smart upfront work.

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jason's curator insight, February 16, 2015 9:58 PM

Great piece on how to tackle big data. 

Luca Naso's curator insight, February 18, 2015 11:17 AM

Nowadays the customer's journey is more complex than the classic "sales funnel", it has several touchpoints and continuous back and forths.
Companies need an automated system to collect, analyse and leverage all of the information produced along the way.

How to do that? Two common methods are:
1. Lead Scoring, to improve efficiency of marketing strategies
2. Predictive Analytics, to anticipate behaviours and improve ROI

clatot's curator insight, February 25, 2015 11:23 AM

Big data is becoming increasingly practical & critical in B2B, with maybe less focus on statistics & more on meaningful usage, to optimise leads & predictive behaviours.

Who has concrete case studies about it ?

 

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Marketing Analysts are Scoring our Future - Gartner

Marketing Analysts are Scoring our Future - Gartner | The MarTech Digest | Scoop.it

► About Us: iNeoMarketing provides Marketing Technology services, applications and support to B2B companies who do not have the required resources, knowledge or expertise. Visit us at ineomarketing.com. ◄

CYDigital/marteq.io's insight:

Although B2C oriented, the point regarding fluidity of scoring is pertinent: does the B2B marketer continually modify its approach to a single prospect based on the score at that point in time, or is the prospect thrown into the bucket of nurturing without any further adjustments based on the change in score?

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How to Drive Adoption of Your Lead Scoring Solution - MarketBridge

How to Drive Adoption of Your Lead Scoring Solution - MarketBridge | The MarTech Digest | Scoop.it

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CYDigital/marteq.io's insight:

This is the appropriate path to take. Note the degree of internal buy-in at various points.

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Lead Scoring's Worst Enemy: Stuff Marketing - CMO Essentials

Lead Scoring's Worst Enemy: Stuff Marketing -  CMO Essentials | The MarTech Digest | Scoop.it

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CYDigital/marteq.io's insight:

Don't expect results when you're attempting to throw stuff up against the wall and expect it to stick. Even half-butt content is better than stuff.

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Comparing Predictive Lead Scoring Vendors | Lattice Engines

Comparing Predictive Lead Scoring Vendors | Lattice Engines | The MarTech Digest | Scoop.it
Being able to trust the quality of predictive lead scores is critical for modern marketers looking to replace outdated, rules-based lead scoring systems. But with so many new predictive lead scoring tools to choose from, how can you figure out which one will deliver the best results before committing to the investment?

Before you begin trying different solutions, be sure to download our latest free guide, Cutting Through the Hype: Comparing Predictive Scoring Vendors.

In this guide you’ll learn how to:

Determine your readiness for deploying predictive scoring

Create training sets of leads for evaluating multiple scoring models

Analyze scoring accuracy beyond just examining conversion lift

Work with providers to build the best scoring model for your goals


Receive a FREE daily summary of The Marketing Technology Alert

CYDigital/marteq.io's insight:

The document doesn't compare different vendors, but provides a framework through which you can compare different vendors. It still doesn't answer the question "how do you know which one is better without loading data?"

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Lead Scoring Strategies for Agencies: Best Practices - Marketing Action Blog - Act-On

Lead Scoring Strategies for Agencies: Best Practices - Marketing Action Blog - Act-On | The MarTech Digest | Scoop.it

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CYDigital/marteq.io's insight:

So long as marketing and sales are at the same table, this should be fairly easy to conquer so long as everyone is using the same vernacular! 

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PQL: Using Predictive Scoring to ID New Qualified Leads - Lattice

PQL: Using Predictive Scoring to ID New Qualified Leads - Lattice | The MarTech Digest | Scoop.it

"We’re using Lattice predictive scores to uncover a new bucket of marketing qualified leads (MQLs). This allows us to continue passing “traditional MQLs” (determined the old-fashioned way using traditional lead scoring) and test a new segment of leads that are deemed qualified due to high predictive scores. This new bucket, which we deemed PQLs or “Predictive Qualified Leads” have high scores for buyer fit (typically account level indicators) but they may not be particularly (or even slightly) engaged.

 

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During our initial roll out, we’re testing this new cohort blindly with our sales team. We still pass our traditional MQLs but we now also pass PQLs that meet a high threshold for predictive score. Our SDR team calls each segment according to the same cadence and SLAs, which should yield some very accurate conversion comparison data. We’ll share the results in a future blog post.

 

The lesson here for me is that marketers need not abandon their activity-based scoring if they feel like it’s working for them. Test it! See how the lead buckets compare."

CYDigital/marteq.io's insight:

A very smart approach, and this is a case study from Lattice (so if they're doing it, perhaps we should as well).

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Traditional and Predictive Lead Scoring: a Match Made in Data Heaven - Marketo

Traditional and Predictive Lead Scoring: a Match Made in Data Heaven - Marketo | The MarTech Digest | Scoop.it
One of the most frequently asked question I hear is: How does predictive lead scoring work with your traditional, existing lead scoring? If you already have lead scoring built into your marketing automation, does predictive lead scoring negate it, or work side by side?

The answer is simple: predictive lead scoring enhances your demand generation funnel and works alongside your existing lead scoring. Traditional scoring is very good at highlighting a prospect’s interest level in your product and willingness to talk to sales, while predictive lead scoring is very good at identifying the ideal candidates for your product.

Think of your traditional lead score as the “activity” fit – the lead’s activities suggest a propensity to become a customer – and predictive score as their “demographic” fit – the lead’s fingerprint matches those of your existing customers. Leads that exhibit high levels of activity but have a low predictive score have a far lower propensity to purchase from you. Leads with a high predictive score, regardless of their activity score, still have a higher propensity to purchase from you.

 

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CYDigital/marteq.io's insight:

Lattice, et al would disagree. If you choose the route of multiple scoring models, consider that you've doubled your management effort.

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