Unkover your competitors’ Marketing Secrets
Say goodbye to wasting hours on competitor analysis by equipping your team with an AI-driven, always-on competitive intelligence platform.
Say goodbye to wasting hours on competitor analysis by equipping your team with an AI-driven, always-on competitive intelligence platform.
Stay Ahead with AI-DRIVEN Competitive Intelligence
Unkover is your AI-driven Competitive Intelligence team delivering critical updates about your competitors the moment they happen:
Track your competitors website changes
Why spend all day stalking the competition when you don’t have to?
With Unkover, you’ll know instantly when your competitors tweak their messaging or shake up their pricing. No more endless scrolling through their sites or second-guessing your strategies.
Let us do the heavy lifting for you, ensuring you’re always in the loop by notifying you the moment a critical change happens on your competitor’s pages.
Sit back, relax, and keep winning—Unkover makes sure you’re not just in the game, you’re always a step ahead.
Read your competitors emails
Companies love updating their customers and prospects about relevant news, product updates, and special offers.
That juicy info from your competitors? It’s yours too. Unkover will automatically capture all their emails and bring them right to your doorstep—accessible to your entire team, anytime.
[COMING SOON: Our fine-tuned AI will sift through these emails, extract key information and send them over to the best team within your org. Less noise, more signal!]
We hear you! Unkover’s goal is not to flood you with tons of data points that no one in your team will ever read. We gather competitive intelligence from thousands of data sources and use AI to highlight actionable information to the right team in your company.
Say goodbye to noise. We’re 100% signal.
ROADMAP
We’re excited to get Unkover in your hands as soon as possible and keep building the best competitive intelligence tool with your precious feedback. The roadmap for the next few months is already exciting, so take a look!
While we build and deliver, here’s our promise to you: as an early tester and customer, you’ll lock in an exclusive bargain price we’ll never offer again in the future.
Spy on your competitors’ full marketing strategy: social, ads, content marketing, email flows, and more.
Track competitive Win/Loss analysis and build battle cards. Get alerted at every pricing change.
Get immediate alerts when competitors announce new features or major releases. Identify strengths and weaknesses from online reviews.
Get the competitive intelligence you need where you need it: Slack, eMail, MS Teams, Salesforce, Hubspot, Pipedrive and more.
slack integration
Unkover’s Slack integration lets you keep your whole team up to speed with your competitors’ updates.
Join now to lock in an exclusive 50% lifetime discount
For startups and small teams, it’s the essential toolkit you need to keep an eye on a select few competitors.
Up to 5 competitors
50 pages monitored
10 email workflows
3-day data refresh
$39
/per month
$ 79
50% discount
Billed annually
For growing businesses, it allows you to monitor more competitors, pages, and email workflows.
Up to 10 competitors
100 pages monitored
20 email workflows
1-day data refresh
$79
/per month
$ 159
50% discount
Billed annually
For large companies, it is tailored to meet the needs of multiple teams needing granular insights.
Custom number of competitors
Custom number of pages monitored
Custom number of email workflows
Hourly data refresh
Custom price
Billed annually
DEFINITION
Lead scoring is the method of assigning points to contacts or potential prospects based on how closely they resemble your ideal customer profile. The higher the lead score, the more likely the lead is to be a good fit for your product or service.
Lead scoring is commonly used by marketing and sales teams to sort through their contact database and reroute the highest quality leads to the sales department immediately–significantly improving their sales funnel.
By implementing a lead scoring system, your sales team can de-prioritize low-quality leads and prioritize leads who have the highest chance of converting. This, in turn, can help to align sales and marketing efforts in a more measurable way.
A lead scoring process can be done through scoring software or manually through spreadsheets–however, the latter can be quite tedious and requires daily maintenance to be accurate.
Predictive lead scoring software takes this one step further and applies big data and machine learning algorithms to scoring to find the right combination of behaviors and data points of existing and potential customers. Then, these attributes are automatically matched and ranked to those of new leads.
Once your scoring system is in place, you can then use your marketing automation tool to send your qualified leads to your team to start the sales process and move leads down your sales funnel.
Through lead scoring, your sales and marketing departments can assign point values to your contacts based on how closely they resemble your ideal customer. Lead scores are then used to determine which contacts should be handled immediately by your sales team and which should go through marketing automation and nurturing campaigns.
Sales and marketing teams who implement a lead scoring system into their process typically see a higher conversion rate, a faster sales funnel, and a higher interest level than those who do not.
While scoring leads manually can be a time-consuming and frustrating endeavor, using good lead scoring software will allow you to uncover high-quality leads and revenue opportunities hidden at this very moment in your database.
Start closing better deals faster, expanding into your customer base and holding on to customers longer (we do retention too)!
Lead scoring is a methodology that sophisticated GTM teams use to rank and prioritize leads. The final score is usually determined by a lead’s behavior, like their interactions with the company’s website and emails, as well as demographic and firmographic information.
In a data-driven context, lead scoring also helps all teams assess the quality of their initiatives (i.e., how effective marketing campaigns are) using an analytical approach to evaluate and rank prospects and lead sales reps to relevant leads faster.
Lead scoring also identifies the best customers, allowing segmentation and targeted outreaches for upsell, cross-sell, and churn reduction.
Scoring is not just beneficial to your sales team. Rather, lead scoring is an important process for both your sales and marketing teams in that it can streamline how marketing pre-qualifies leads and make any sales team more efficient by following up with the right leads at the right time.
When setting up a lead scoring system, you’ll be able to:
The reality is that no two leads are exactly the same. This is where lead scoring comes into play–it helps to surface differences, enabling sales reps to know who they’re communicating with and whether they should have that conversation at all.
When using manual scoring, sales and marketing teams manually assign point values or scores to leads based on their potential to convert into customers. This method can be time-consuming, subjective, and prone to errors.
On the other hand, predictive lead scoring is a data-driven approach that applies big data and machine learning algorithms to scoring to find the right combination of behaviors and key attributes of existing and potential customers in real-time. Then, these attributes are automatically matched and ranked to those of new leads.
AI & Lead scoring
Breadcrumbs leverages a machine learning-assisted approach for lead scoring, which combines the power of AI algorithms with human expertise. This unique approach enhances the accuracy and effectiveness of scoring by leveraging the insights and intuition of experienced sales professionals.
Whether you’re using manual or predictive scoring, there are different outputs you can get:
To have the most comprehensive lead scoring strategy, we recommend using predictive lead scoring with a co-dynamic approach.
Predictive scoring tools like Breadcrumbs also add recency and frequency data points into the lead score equation, which allows you to find qualified leads at the exact time they’re ready to purchase and results in converting leads at a faster rate.
Let’s see each of these factors and how lead scoring works when using a co-dynamic approach:
Fit refers to how well a prospect matches your ideal customer profile (ICP). This is determined by explicit data gathered directly from the leads through lead generation or contact forms–demographic and firmographic information like job title, industry, or revenue.
For B2B software companies targeting mid-sized tech companies, a CTO from a tech company with 200 employees would be a strong fit. The closer a contact aligns with your buyer persona, the higher their fit score, indicating a higher likelihood of conversion based on their profile alone.
On the other hand, Activity is about what the contact does. It involves tracking and scoring a lead’s behavior or engagement with your company. This is determined by implicit data, which includes actions like email opens, website visits, content downloads, etc.
A contact who visits your pricing page often may receive a high engagement score, indicating buying intent. Likewise, a contact who downloads a whitepaper may receive a higher lead score compared to someone who only visits a blog post.
An effective scoring model combines ‘Fit’ and ‘Activity’ scores to give a comprehensive view of a lead’s potential.
A tool like Breadcrumbs provides a clear breakdown of what fit and intent data was used to generate every score, offering deep insights into the quality of leads entering and progressing through your sales funnel.
Recency is based on recent engagement with your business. This could include visiting your website, clicking on email links, downloading resources, or interacting. The principle is simple: Contacts who have recently engaged are more likely to be interested in your products or services than those who haven’t engaged for a while.
A prospect who visited your pricing page yesterday would receive a higher score than someone who last visited a month ago. The more recent the activity, the higher the score, signifying increased interest and a greater chance of conversion.
Frequency is about how often leads interact with your brand. It measures how many times a prospect engages with your business. Prospects who frequently visit your website, open your emails, or interact with your content are likely more interested than those who rarely engage.
A prospect who visits your blog every week and regularly downloads resources would be assigned a high score. This frequent engagement suggests a deep interest in your content and a higher potential for conversion.
A comprehensive lead scoring model should consider both recency and frequency. A prospect who recently and frequently engages with your brand is likely highly interested and potentially ready to purchase. By factoring in these aspects, businesses can prioritize their leads effectively, focusing on those most likely to convert.
Time Decay in lead scoring refers to the decrease in the value of a lead’s action over time. The underlying principle is that the more recent an action, the more relevant it is, leading to higher scores. Conversely, the score for past actions decreases as time passes without any new engagement from the lead.
If a lead visited your pricing page two weeks ago but hasn't engaged since, their interest in your product or service might be waning. Their score for that action would decay over time, indicating they may be less likely to convert than a more recent prospect.
Time Decay is useful for tracking and scoring a lead’s activity data. When combined with frequency and recency of engagement, it allows you to maintain accurate and up-to-date scores. This approach helps your marketing and sales teams identify the engaged leads and lets you spot prospects whose interest might be diminishing.
Implementing Time Decay in your lead scoring model involves regularly updating lead scores based on their ongoing activity. A scoring system like Breadcrumbs can automatically adjust scores over time, ensuring that your lead scoring models remain accurate of each lead’s current level of interest.
Lead scoring criteria are customer data points you use to create a lead scoring model and rank leads. This can include demographic, firmographics, activity, intent, and behavioral data.
While you may think you need many scoring criteria to create your model, the truth is that you can get started with just a few pieces of contact data that already exist in your database.
Demographic data is information about a particular person, while firmographic data is information about a company or organization. Examples are:
This data includes how engaged users are with your website or product and what activities they are doing that signal interest and buying intent (i.e., view pricing or product pages, open emails, and so on.) Examples are:
The first step of creating a comprehensive scoring system is to define your point values and model criteria. The old-school way to do this is to work with your sales reps and marketing team to figure out which characteristics typically indicate a higher intent to purchase.
These indicators can be found in a variety of ways–by looking at the demographics and firmographics of your current customers, reviewing the online behavior of these contacts on your marketing analytics, conducting customer interviews with your existing customers, and looking at your best-closed deal(s).
This is time-consuming and difficult to implement. Using a data-driven automated approach, such as the one we have built Breadcrumbs on, will save you time and still give you all the information and control you need to make critical business decisions.
I can tell you from experience, you likely already have all the information you need to create a lead scoring model, but that information is scattered across multiple data sources. By unifying this data and applying machine learning algorithms, you can quickly build a scoring system that predicts customer intent and helps you make more efficient business decisions.
It’s easy, it’s quick, and you can start for free:
Want to see Breadcrumbs in action? Book a 30-minute demo with a revenue expert.
There are a few key points to ensuring your lead scoring models qualify leads efficiently and create accurate and actionable results.
The quality of the data you input into your lead scoring models is crucial. High-quality data helps you find out where prospects are in the customer journey and let sales teams know if they are ready to buy and the right time for the lead handoff.
While there is no such thing as perfect data, here are some of the best practices to evaluate the quality of the data you’re providing your scoring models include:
You may be wondering if you have enough data. The reality is that all you need are 5 to 9 data points to build an excellent predictive scoring model.
One of the unthought-of things about this exercise is that you can frequently unearth activities and/or fit attributes on your lead that you didn’t know would significantly impact scoring!
The honest answer is it depends on what type of scoring approach you’re using. With a numerical output, where you assign points to specific attributes or actions, once your leads reach a point threshold (let’s say 50), they’re considered qualified and sent to the sales team.
What is a lead score threshold? A lead score threshold is a predefined score at which a lead is considered qualified enough for direct sales follow-up. It is essentially a cut-off point used to determine when a lead moves from marketing to sales or from a nurturing track to active engagement.
The sales rep that gets a lead assigned, though, doesn’t know what made up the lead score (i.e., the lead interacts with your product vs. they’re from a company in your ICP) and can’t personalize their outreach.
If you’re using a co-dynamic approach, on the other hand, you have 16 different combinations of fit and activities (with A1 being the most qualified lead), and you’re able to use marketing automation to route each scored lead toward the right team or action based on the exact factors that made up their score.
Here’s an example when scoring leads for acquisition (the goal is to get them on a demo call) to see what I mean:
While you may be surprised to see D’s listed here, these contacts are highly engaged, and it’s not something to be taken lightly. You shouldn’t disqualify them entirely, even though they fall outside your ICP.
Direct these to your sales team with the highest priority—these leads are highly engaged and looking into your service right now.
The next segment can be a little trickier to tackle. These contacts aren’t completely interested, but they’re not ready to take the next step just yet. A good idea would be to get the contact to raise their hand and indicate if they’re ready for the next step.
Direct them towards content that’s more towards the bottom of the funnel—think case studies, competitor comparisons, etc. Getting these contacts to download or interact in any way with this type of content is a good sign that they’re getting closer to being ready to see your product in action.
At long last, we get to the bottom of the pack. While you may want to toss these leads and contacts altogether, fear not—these people just need a little more coaxing. The next set of tactics will focus on nurturing the contacts into the A3-D3 bracket.
If you have a BDR on your team, this is likely the type of contact they’d interact with first. Get a conversation going by reaching out and personalizing your messages to address their main pain points.
This approach can be used for different scoring goals (free trials, upsells, cross-sells, churn reduction, just to name a few.) What to see more? Let’s chat about it.
Conducting a lead scoring analysis is crucial if you want to ensure your sales and marketing efforts are effectively prioritized and targeted. By analyzing your lead scoring system, you can:
By performing lead scoring analysis, you’re not just verifying the efficacy of your lead scoring model but also continuously improving it. This ongoing refinement leads to better-targeted marketing efforts, more efficient sales engagements, and ultimately, higher conversion rates. It’s a key practice for maintaining the effectiveness of your lead qualification process.
Lead handoff is the process of handing over marketing leads to sales so that the sales team can nurture, qualify, and convert them into paying customers.
In order to optimize the marketing-to-sales handoff and ultimately increase conversions, you need to get clear on Sales and Marketing funnel terms, define handoff requirements, and analyze, review, and improve the process over time.
However, making sense of the data coming from different parts of your organization that often don’t communicate with each other (hello, silos!) is impossible to do at scale unless you use a tool that is able to connect the dots between all your data sources and give you actionable insights into revenue acceleration opportunities.
Data enrichment works hand in hand with lead scoring by enriching existing customer scores with additional information that helps teams better target and personalize experiences for prospects. This data is used to review each lead’s profile and glean insights about their behavior, preferences, location, interests, and other factors that contribute to the decision-making process.
The key benefits of data enrichment are:
Contact scoring is a technique for ranking contacts in your database based on criteria such as company data and how recently they’ve engaged with you. It also helps you discover high-value prospects, re-engage clients you may cross-sell or upsell to, and gather inactive clients before they permanently go.
You can use contact scoring to:
The best contact scoring tools will look at an individual’s primary demographic and firmographic data ( job title, no. of employees, industry) and also factor in the following time-sensitive criteria, such as engagement data, recency and frequency of action, and time decay.
A contact scoring software like Breadcrumbs leverages first-party and third-party data to crunch the numbers using machine learning to determine when you need to take action.
We’ll combine data from all of your touchpoints (your CRM, marketing tools, and existing product usage tools) to give you a comprehensive view of what activities and behaviors are driving behavior.
What’s the next step? Let’s talk about how to define your objectives and develop models that produce actionable scores you can use to drive processes and activities (i.e., in-app messages, email campaigns, sales outreaches), increase leads, and boost revenue acceleration.
Start closing better deals faster, expanding into your customer base and holding on to customers longer (we do retention too)!
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