Product life cycle is a term used to describe the stages of creation, growth, and retirement that any product goes through as it makes it way to and through the hands of its users. The traditional stages are a product life cycle are development, introduction, growth, maturity, and decline.
The product life cycle lives mainly in the hands of Product Managers and marketing teams. Marketers and Product Managers use the stages of a product life cycle for related, but different reasons. Marketers use product life cycle to create marketing strategies that will reach a broad audience of consumers, to brand as well as to determine product pricing. Product Managers use product life cycle to evaluate development resources, investment and maintenance in a product or feature.
The product life cycle stages
Ideation is the informal beginning to the product life cycle. It begins with an idea that is formed into a concept. Ideation is the process that includes evaluating the goals for the new product, market fit research, market demand, competitive analysis, usability research, potential revenue opportunity, and potential costs. Many parts of the organization are typically included at this stage including Marketing, Product, Engineering, Design, and the organization’s leadership.
Development begins after market demand is assessed and ideation has resulted in a formalized plan for a new product. Artifacts of the development stage include final designs, written requirements, and acceptance criteria. Engineers, Product Managers, UX Designers, QA Analysts are typically the main contributors at this stage. Marketers find themselves in the strategy stage as the product enters development and they begin planning market positioning and pricing for the Introduction stage.
Introduction begins after development is complete. In an Agile framework, “complete” can be relative and introduction would begin as soon as a workable product is available for use. At this stage, the market will be introduced to the product for the first time. Many times, marketers take the lead in introducing the new product to the marketplace based on the strategy they created during the development phase. The introduction strategy includes which segment of the market they intend to reach, what channels and ways of advertising will be used to introduce the new product, and what messaging will be used when marketing to consumers.
Growth is the stage where customers are adopting the new product. Product adoption is continuing to rise and profits increase. Sales teams may even be incentivized to sell the new product prospects and existing customers. Development teams are typically continuing to make changes and enhancements to the product throughout the growth stage. Teams are monitoring the product for the achievement of the goals they set during ideation. The product is still receiving investment in the form of marketing and development efforts.
Maturity is reached when product adoption is no longer growing at an exponential rate and has reached its market saturation. Teams may decide to continue to invest in the product in order to remain competitive, or they may leave it unattended while they focus on other earlier stage product efforts. Many times at the maturity stage, the product is receiving at least minimal development for maintenance but marketing efforts have become minimal.
Decline is when the market no longer needs the product in the same way that it did during the earlier stages of the product life cycle. Customers are leaving the product and sales are likely declining. Many teams decide to stop supporting the product during the decline stage and they will abandon the product or they may decide to remove it from the market altogether. This happens when customer usage declines to a low percentage of the overall customer base. Some teams may reinvent the product at this stage by adding new features, finding new market segments for the product, or repackaging the product to allow for new marketing efforts. Whether the product is abandoned or reinvented, letting a product reach the decline state allows the team to focus on the product life cycle all over again.
The importance of managing a product’s life cycle
Understanding the product life cycle is critical for both product and marketing teams, as well as the broader organization. The stages help teams understand what level of investment a product should be receiving, which products in a company’s portfolio should have the most focus and investment, and which products have the most opportunity for growth, revenue, and profit. Life cycle management impacts many teams in the organization, most notably sales, marketing, and product development. The product life cycle framework helps teams make tough decisions about existing products while helping new ideas grow.
The buyer’s journey has never been more complex. With new technologies are drastically revolutionizing the way we market and purchase products, it’s no longer as simple as a customer walking into your store and buying something they need.
Nowadays, consumers are inundated with ads on their phones, laptops, TVs, and, of course, billboards. More choice for them means more competition for you. To stay competitive, businesses need to be highly strategic about how they identify and interact with their prospects.
That’s where MQLs (marketing-qualified leads) and SQLs (sales-qualified leads) come in. It’s highly probable that you’ve heard of these two acronyms before. But what differentiates the two? And why do they even matter?
Throughout this post, we’ll also explore why lead qualification and lead scoring are such critical business practices, the nitty-gritty criteria which set MQLs and SQLs apart, and how to nurture an MQL into an SQL.
What are MQLs?
If you haven’t already, read our detailed guide to MQLs here. But if you’re short on time, here’s the gist of it.
Marketing-qualified leads have demonstrated an interest in your company and your products. They’ve usually intentionally interacted with your brand by taking part in some sort of quid pro quo exchange — they leave their contact details in exchange for promotional emails, a resource download, or a webinar sign up.
But not everyone who demonstrates an interest in your company automatically becomes an MQL. In some instances, they’re not the right leads to be going after (more on this later).
However, if they do fit your lead qualification criteria, then they can be accepted into the sales funnel and classified as a marketing-qualified lead.
Once a marketing-qualified lead has been identified, it’s now the marketing team’s job to lead them further down the funnel until they’re ready to speak directly with the sales team (and hopefully purchase).
What are SQLs?
SQLs are further down the funnel than MQLs — they’ve usually been nurtured by the marketing team’s efforts and are now closer to purchasing than they were previously.
Once they’ve demonstrated a significant interest in your products, it’s now the sales team’s job to close them. Simple as that.
Of course, not all SQLs are created equal. Someone who fills out a form immediately requesting a demo is probably a hotter lead than another prospect who visited your website multiple times but over a long period of time.
It’s also useful for a salesperson to know which particular pain-point their leads are trying to solve. Usually, this information can be gathered by analyzing the lead’s interactions to date with your organization.
Which of your social media ads did they click through on? Which of your marketing emails did they open? Which website pages did they visit? Which forms did they fill out?
This, provided with some general lead qualification data (industry, age, position, etc.) should give the salesperson all they need to contact the prospect with confidence.
Differences between MQLs and SQLs
Essentially, MQLs and SQLs aren’t all that different — they describe a prospect who’s shown interest in your company, but for whatever reason hasn’t yet become a customer.
The main difference between them is how far along their buyer’s journey they are, and which of your teams are responsible for handling them.
As you might imagine, the marketing team is in charge of MQLs. These are top- or middle-of-funnel prospects who aren’t very far along in their buyer’s journey. They require a softer, more generalized approach than prospects who are further along the sales funnel.
At this stage of the sales funnel, you need to steadily raise their awareness of your organization and pique their interest in your products. You’re also acquiring data so that you can work out what precisely they need and tweak your marketing outreach accordingly.
Once a prospect has shown enough continued interest to be classified as a bottom-of-funnel SQL (we’ll delve into more detail later on about how to properly make this distinction), they’re then passed over to the sales team to complete the sale.
The principle of lead qualification
Before you can classify a lead as an MQL or an SQL, you need to first make sure they’re worth pursuing. As a business, you don’t want to waste time, money, and effort going after people who won’t actually end up purchasing anything — this is where lead qualification comes in.
Lead qualification refers to the strategy that businesses have in place for identifying potential leads and nurturing them into becoming customers.
You basically want to work out whether or not:
- The prospect is in the right industry or company for your product
- They have pain points which your products can solve
- They’re in a position to make buying decisions
If prospects don’t meet these criteria, then you should automatically disqualify them. Sure, it feels good to have lots of people interested in your products. But if they’re ultimately never going to purchase, there’s little point in trying to convert them.
Ineffective (or nonexistent) lead disqualification can have a worrying impact on organizational morale. You don’t want your marketing and sales teams constantly coming up against people who simply won’t ever become buyers.
Not only is it a waste of resources, but it also prevents your team members from succeeding at their roles.
How to score MQLs and SQLs
Qualified your leads as valid prospects? Great. Now it’s time to engage in a lead scoring process to figure out exactly how far along the funnel they are.
As the name suggests, lead scoring involves giving each lead a score (usually out of 100). In general, the higher the score, the further down the funnel — and the closer to purchasing – they are.
Lead scoring gives you a quantifiable, standardized measurement for classifying each lead as an MQL or SQL.
Leads can be scored on a variety of potential actions: the number of times they’ve visited a website, the percentage of marketing outreach emails that they’ve opened, if they’ve downloaded a whitepaper, or if they filled out a form asking for a demo.
This list is by no means exhaustive. For example, a prospect attending an event is also an indication that they’re interested in your products. It’s up to each individual company to decide which specific actions would affect a prospect’s lead score.
Before creating your lead scoring process, it’s important that you deeply analyze your company’s customer history.
For example, do you find that people who click on LinkedIn ads are more likely to purchase than those who come via Facebook? Do event attendees more readily convert than those who download your whitepapers?
This is where your company data is vital. The more you know about your prospects, the better. For B2B businesses, you’d ideally know which company they work for, how large it is, where it’s located, and which industry it’s in.
Once you have a tangible measurement outlining where a prospect is in their buying journey, you can then classify them as either an MQL or an SQL — and pass them off to the marketing or sales teams.
What you need to decide
It’s critical that sales and marketing come together to determine what makes an MQL/SQL, and how to approach each of them. It might even be worth drafting up an SLA (service level agreement) which provides answers to the following questions:
- What’s each team’s objective? Is the marketing team focused on the number of SQLs but the sales team on revenue? Keep your team’s overarching goal in mind — this will help when fine-tuning both your lead generation and lead qualification processes.
- What precise lead score makes an MQL? Or is an MQL any qualified lead that hasn’t yet converted?
- How do you follow up with an MQL? How quickly do you follow up on any new leads, and how do you get in touch with them?
- How many follow-up attempts do you make before an MQL is downgraded back to being a prospect?
- What precise lead score makes an SQL? What does an MQL need to do to become an SQL?
- How will you maintain ongoing communication between sales and marketing teams? Sales needs to let marketing know what makes a good prospect, and marketing needs to alert sales as to each prospect’s pain points, the content they’ve consumed, and what their buyer journey to date looks like.
How do you know when an MQL becomes an SQL?
Working out how and when MQLs turn into SQLs is a complex process. If you send leads across before they’re ready, they probably won’t end up converting — and you’ll incur the wrath of your sales team.
However, if hot leads are left languishing for too long without speaking to a sales representative, then they may start to look elsewhere.
This is an ongoing process that requires constant dialogue between marketing and sales teams. Ideally, marketers should pique a prospect’s curiosity, increase their interest in the company and products, and get them to confirm themselves that they’d like to be passed over to sales (by filling out a demo form, for example).
There should also be a clear cut-off in your lead scoring process where MQLs become SQLs. For example, an MQL might have a score of 40+ (out of 100), and anyone who has a score of 80+ becomes an SQL.
Each time that an MQL visits the site, their score increases by five points. Each time they click on a link from a marketing email, their score increases by 10 points. If they fill out a demo form, they are automatically passed over to sales.
Once you’ve decided how you’re going to weigh each touchpoint, map this out in your CRM (or marketing automation software) and let it automatically take care of the rest.
By assigning a numerical score to your leads, you avoid having to rely on sentiment. It’s hard to know how ready someone is to purchase according to how you feel — it’s far more accurate to use a standardized, agreed-upon, organization-wide measurement.
Why do MQLs and SQLs matter?
Without clear parameters outlining who’s an MQL and who’s an SQL, the entire sales process would be a messy melee with different teams bombarding the same prospects from different angles.
You don’t hire marketers to close sales. Sure, if they do then that’s great — but their job is to raise awareness of your brand, pique your prospects’ interest, and get them excited about potentially buying your products.
Likewise, you don’t hire salespeople to raise awareness or interest. Salespeople are there to aggregate all the information you have on a prospect, tailor their pitch accordingly, and close a sale.
Simply put, lead qualification ensures that marketing and sales teams have clear boundaries — that they know which prospects to go after and at which stage of the buyer’s journey. By properly scoring and assigning MQLs and SQLs, you’ll keep your sales and marketing engine organized and effective.
The post MQL VS SQL: How to define lead types in marketing and sales appeared first on CallRail.
A partner portal – whether it’s a PRM or a homegrown system – can be an amazingly effective way to empower your team with the tools and resources it needs. But like any system, it needs regular monitoring and maintenance to make sure everyone’s reaping maximum benefit from it.
Because your portal is partner-focused, there’s no indicator more vital or telling than whether your partners are actually using and benefiting from it. Luckily, a modern and insightful partner portal gives you the power to monitor the clues your channel partners are giving about their engagement. This knowledge will give you confidence when things are going well and the intel to tweak and evolve your portal when they aren’t. What should you be looking out for? Here are some of the KPIs that will help you consistently measure engagement – and thus, the overall effectiveness of your partner portal.
How many times a partner logs in to the portal.
A partner can’t be engaged if they aren’t using your system regularly – or even worse, not logging in at all. That’s why the very first thing you should be tracking is whether your partners are actually logging in to your portal, and how often. If they aren’t logging in, you need to encourage them and that probably means improving your to-partner marketing.
Tip: If you need your partners to log into your portal more, try incentivizing them to check out new content sales enablement playbooks on a weekly basis (or whatever you decide). This way, your partners are more inclined to add logging into your portal to check out company updates on a more regular basis.
The amount of times they’ve been in contact with your partner team.
Hearing crickets? That’s a bad thing. Typically, an engaged partner will be reaching out to you. A potent, automated onboarding process will naturally eliminate some of that outreach because basic questions will be already covered. However, you can expect that engaged partners will come to your team with more advanced requests like guidance on the right prospects to go after and feedback on how they’re performing. If you’re surrounded by the sound of silence, ask yourself why. Do partners know where to go for help and questions? Is it easy for them to reach out? Are you creating a welcoming, open and collaborative atmosphere?
Tip: If you need to increase the frequency of communication between your partners and you, try creating processes around meeting cadence and check-ins. If there’s a standard meeting on the calendar for a status update, it could open the door for better conversation or eliminate confusing processes your partners may be experiencing.
How many learning tracks or pieces of training they’ve completed.
A thirst for knowledge is a great indicator of engagement. If a partner is fully on board, they’re going to want to continually learn and grow with you. Keep an eye on the learning tracks or training they’re completing in your partner portal. Make sure partners know and understand the learning resources available to them and foster an environment that promotes continuous education and improvement.
Tip: Increase learning tracks and onboarding certification completion through gamification. Who doesn’t like incentives?
How much content they’ve viewed, shared or downloaded.
You can have a whole library of resources on your partner portal, but if partners aren’t using it, it’s useless. The more content they view, the more they know about your company and the better brand ambassadors they become. Keep an eye on what they’re viewing and using. If content isn’t being used, ask yourself why. Is it a matter of to-partner marketing, or is that your content needs an overhaul?
Tip: Alert partners when new content is uploaded to your portal. This is a good reminder for them to engage with relevant collateral you spend time creating.
How much content they’ve co-branded.
The power of co-branded content is strong – it’s the most effective way for partners to solidify their connection to your brand in their prospects’ eyes. Although not all partners should be able to co-brand content, it’s important to keep an eye on those that can. Are they using the full functionality of your co-branding resources? If not, ask yourself if they fully understand its power and if your process is simple enough.
Tip: Give them co-branding ideas and use cases to help increase the volume of content co-branded.
Look at it in totality.
Now that you’ve examined engagement levels at a granular level, take a step back and look at the big picture. The simplest way to track overall channel health is to look at the percentage of your partners that are engaged. If overall partner engagement is dropping, it may be a sign that you need to revamp your strategy. If engagement is on the rise – give yourself a pat on the back, you’re doing it right! Either way, never stop keeping a close eye on engagement. A portal is your partners’ home base. Make sure it’s always giving them what they need to succeed.
The post These KPIs Will Tell You if Your Partners are Truly Engaged appeared first on Partner Relationship Management Software (PRM).
Customer Lifetime Value (CLV) is the total value in revenue a customer represents to a company over the entirety of their business relationship or customer life cycle. It is one of the most important metrics to track for overall business performance.
The importance of measuring CLV
Customer Lifetime Value (CLV) can be one of the most important metrics for you to track in your business for a host of reasons. Three of the most important reasons to track CLV include, but are not limited to:
- Developing marketing strategy & measuring marketing performance
- Building effective revenue projections for your business
- Assessing your company’s valuation
Customer Lifetime Value (CLV) is sometimes used interchangeably with Lifetime Value (LTV), and is a current projection of future revenue. In the strictest sense, CLV is the present value of the future cash flows attributed to the customer relationship.1
In the case of marketing, understanding CLV is possibly the most important metric that you need to understand in order to make both strategic and tactical decisions. When evaluating how your business is going to acquire new customers, and how much you are willing to pay to do so, it is essential that you understand exactly what a customer is worth to the business so that you are not exceeding that value with your marketing efforts. Quite simply, Customer Acquisition Cost (CAC) cannot be greater than Customer Lifetime Value (CLV). Remember, marketing is a driver of growth and revenue in a business, not a cost center. If your marketing efforts are not generating a profitable return on your investment, you are doing marketing wrong.
Customer LTV for repeat purchases
For example, assume that you run an e-commerce website and your average order value is $25 and your margin is 50%. If you know that on average a customer will return to purchase from you again 6 times over the course of the next two years, then you know that your CLV is $75. (($25 * 50%) * 6) = $75 Armed with this knowledge, you know that you can confidently spend $18.75 to make that first sale, even though $18.75 is greater than your profit on that initial purchase ($25 * 50% = $12.50), because that new customer will likely continue to purchase from you five more times over the next two years, resulting in Marketing Return On Investment (MROI) of 400%, which is a solid return on marketing investment.
Customer LTV for recurring revenue Models
In the case of subscription-based companies, or recurring revenue business models, if a customer spends $10 per month and has an average lifecycle of 4 years, a 75% profit margin will result in a Customer Lifetime Value of $360. This means that as a marketer you can spend as much as $90 to drive that initial customer conversion of $10 and still see a 4x return on your marketing investment. This is one of the reasons that recurring revenue business models are so attractive for business owners and investors as it leads to a long-term relationship and supports a base of loyal customers.
Using customer lifetime value to develop marketing strategies
As an intelligent, data-driven marketer, knowing your CLV and comparing it to your Customer Acquisition Cost (CAC) is a smart way to evaluate the effectiveness and efficiency of your individual marketing tactics and channels. However, CLV also plays a critical role in strategic development, and this is where the power of customer segmentation really moves the needle for marketing performance.
Segmentation is effective in part because delivering marketing messages to specific & similar groups of consumers allows marketers to increase messaging relevancy and speak to unique consumer pain points. But customer segmentation also drives strategy when the concept of CLV is applied to understanding customer cohorts and what groups of customers a business should seek to acquire. Whether you are segmenting by demographic characteristics (such as age, gender or geographic location), firmographic fields (ie. industry, employee size or revenue), or behavioral factors (ie. recency/frequency of purchase), your segmentation matrix is incomplete without understanding which are your most valuable customers. When you have accurately identified your most profitable customers, you can focus your marketing efforts on attracting those specific customer segments, improving your likelihood of producing a positive MROI.
This critically valuable information can also inform business managers and product or service developers as they evaluate the future direction of the business. This kind of insight is at the heart of what is called consumer-centric marketing or marketing-led business development.
How to measure customer lifetime value
While this metric is typically expressed in terms of an average and based on past customer data, in certain circumstances it is used in one-to-one relationships and can be a fixed, known number, such as in contract sales or one-time purchases.
Lifetime value calculation
CLV = Margin ($) * (Retention Rate (%) / 1+Discount Rate (%) – Retention Rate (%) )
CLV = (ARPU ($) * Margin (%) ) / Churn Rate (%)
CLV = Revenue – (COGS + Cost of Services)
Customer Lifetime Value (CLV) is almost always calculated as the value after gross margin, or the actual profit attributed to a customer after the cost of delivering the service and the Cost of Goods Sold (COGS), the raw inputs that go into creating products. Sometimes CLV can include the Customer Acquisition Cost (CAC), how much must be spent on the process of acquiring a new customer, or a similar metric such as Cost per Acquisition (CPA), the average cost of acquiring a customer, into the calculation2. But in other cases, CLV is weighed against CAC metrics to evaluate the effectiveness and efficiency of marketing and sales efforts.
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Time-decay attribution is a multi-touch attribution model that gives some credit to all the channels that led to your customer converting, with that amount of credit being less (decaying) the further back in time the channel was interacted with.
The assumption here is that the first advertising channel your customer interacted with merely planted the seed, and the customer’s interest in committing to a purchase grew over time with repeated exposure to various marketing channels. As such, the way that the time-decay attribution model assigns credit to your different channels can be interpreted as a rising level of interest and commitment from the customer.
Application of the time-decay attribution model
1. First, a friend mentions an old movie, and I think “I wonder if a t-shirt exists for that?” – this leads me to an organic search for the item on my phone during a lull in conversation. I see a few different options. I click one, but when my friend wants my attention again, this passive activity ends as I close the window and return to being present. I would not remember my fleeting desire for this shirt.. unless I was somehow reminded..
2. Two nights later, I’m scrolling through my Instagram feed before bed. (We’ve all seen the studies on electronics usage affecting sleep. That doesn’t mean people don’t do it.) Between pictures of my friends’ pets and what they had for dinner, an ad appears for the site I went to earlier. I go to it again. I wisely decided that I shouldn’t make a purchase while half-asleep, but the item is more firmly lodged in my brain at this point.
3. At work the next day, I scroll through Facebook after a string of meetings to give my brain a break. Surprise! There’s another ad for the site. I go back to show my co-workers the shirt for the social approval I need before making a $20 purchase. They co-sign on it, but as a responsible employee, I then get back to writing articles like this one.
4. The following evening, I’ve decided to pull the trigger on my new t-shirt that will proudly display my knowledge of obscure film. By this point, I remember the site’s name, which would have been in doubt after my first (or even second) encounter with it – thanks, advertising! I make a direct visit to the site while fully lucid, I complete the transaction.
I became a conversion, and my conversion path was:
Organic Search (4 days ago) -> Instagram (2 days ago) -> Facebook (1 day ago) -> Direct visit
Using the time-decay attribution model, this effectively reads as the journey from curiosity to taking action. For any math-inclined readers, the basic formula involved is y = 2(-x/7), with the results then converted proportionately to fit into a neat 100%. Accordingly, the conversion credit break down as:
Organic Search: 19.8%, Instagram: 24.1%, Facebook: 26.6%, Direct: 29.4%
Of note, this illustrates how important the time aspect of this model is: the above example plays out over four days. Many purchases beyond a $20 t-shirt take much more time to consider, so the difference in conversion credit percentages above becomes much more drastic the longer the customer journey is.
Since this t-shirt cost the company $4.50 to make, the profit is $15.50 for the sale. The time-decay model gives Facebook ads spend credit for 26.6% of this profit:
$15.50 * 26.6% = $4.12
And, Instagram gets 24.1% of the profit:
$15.50 * 24.1% = $3.74
Using a hypothetical cost of $1.70 per click for Instagram and $1.05 per click on Facebook, we can see that in this case the lower value spent on the Facebook click drove more value. This helps make the decision to maintain or raise the Facebook Ad spend.
To be more accurate, the example would include other business costs, lifetime value of customers and be applied across many purchases and customer touchpoints to measure overall profitability.
Pros and cons of using a time-decay attribution model
- Sharing is Caring. Gives some credit to all touchpoints
- Always Be Closing. Touchpoints closest to the conversion are valued the most, which gives preference to marketing channels that tend to do more of the “closing” work
- Consistency is Key. Applying a standardized formula to all of your campaigns will easily highlight fluctuations in the activity of individual channels
- Didn’t See You Back There. Gives less credit to the first touchpoint, which might be the most difficult to execute
- One Size Doesn’t Fit All. Customer journeys are not always a straight line, so the path they took may not be best represented by lowest to highest value interactions
- Hard Numbers. The math involved, while consistent, could be a little complex
Time-decay attribution is especially helpful to measure longer sales cycles, as time between channel interactions will really serve to highlight the difference in conversion credit they receive. Timed campaigns also do well under this model since the time measurement aspect is what this model is based around. Consistency is also a major benefit, since the y = 2(-x/7) formula is standardized, so fluctuations in activity are easily measurable. By using a set formula that uses the number of days prior to conversion as a key variable, every marketing channel receives credit based on the assumption that the more time that has passed since the first interaction, the closer the customer got to the actual sale.
Defining and identifying marketing qualified leads (MQLs) is the catalyst for all marketing efforts. In this piece, we’ll explore what an MQL is, how they can be qualified, the relationship between MQLs and SQLs (sales-qualified leads), and how MQLs can help show return on investment (ROI).
What is a marketing-qualified lead?
A marketing-qualified lead is a prospect who has expressed a certain level of interest in your company’s products or services.
If we think of the classic sales funnel — with top-of-funnel being those who have never heard of your company before and bottom-of-funnel those who are about to purchase from you — MQLs are roughly halfway along.
MQLs have all interacted with your brand in some way, shape, or form — be it by downloading a whitepaper, attending a webinar, or adding items to your ecommerce store’s basket. These actions indicate that they’ve taken the very first steps to becoming a customer.
Once a prospect has been identified as a lead, it’s the marketing team’s job to appropriately nurture them — leading them further down the funnel until they become an MQL, and can be passed over to sales.
At that point, the sales team come in and close the deal. In general, MQLs become SQLs, but we’ll cover that in more detail later on.
There’s often a quid pro quo exchange when prospects become MQLs. In most cases, they agree to give you their details — email address, company (if applicable), phone number, etc. In return they get something of value, like a piece of content that addresses one of their pain points, or problem solves for them.
How to define marketing-qualified leads
Your lead generation process might not be too fine-tuned — it might focus more on generating as many leads as possible rather than necessarily generating the right type of leads. Typically marketers try to cast as wide a net as possible to build out a lead database, and then dial in with targeted outreach (nurture campaigns, email programs, content campaigns), to try to turn those leads into MQLs.
Because of this, all leads that come in have to be qualified before you begin marketing to them. The initial step to qualifying a lead is seeing whether they match certain demographic criteria.
For example, are they from your target region? Do they have a pain-point that your products can solve? If the answer is yes, and if they’ve demonstrated an interest in your company, then they’re ready to be nurtured by the marketing team.
There are no set criteria for classifying an MQL — it totally depends from business to business. However, what’s certain is that the sales and marketing teams need to work together closely when identifying MQLs and SQLs.
Marketing and sales need to decide how warm a lead should be before it converts from being an MQL into an SQL. Too cold, and hard sales tactics may end up putting the customer off. If they’re too warm for too long, and marketing doesn’t pass them over to sales, they may lose interest and opt to do business with a competitor instead.
Lead scoring has a key role to play in this process. Each lead that comes in should have their own numerical score indicating their position in the buyer’s journey. The higher the score, the closer they are to purchasing.
When a lead performs a certain action — be it clicking through on a marketing email, signing up for a webinar, or requesting a demo — a certain amount of points are added to their score. And once they reach a certain score (indicating a high level of interest in your company) they then become an SQL and are passed over to sales.
Bear in mind though that lead scoring (and qualification more generally) doesn’t have to be manual. Using a piece of marketing automation technology will make this whole process far easier and more efficient.
But first off, what are the key things to look for when defining what makes an MQL?
1) Customer history
In general, the first thing you should do is look at historical customer data. Once you know how previous customers behaved prior to purchasing, you can more easily predict which of your current leads will become buyers.
See if any key trends keep on cropping up when analyzing previous customers’ buying journeys. To make this analysis as accurate as possible, it’s best to use an attribution model.
If you’re lucky, a strong trend may well emerge when looking at previous customers. Perhaps the majority visited your website’s pricing page before signing up to receive email alerts, or clicked through 5 of your marketing outreach emails, before requesting a demo, and finally purchasing.
In this case, you have a nice and simple buyer’s journey to form the basis of your lead scoring — and lead qualification — process.
2) Target personas
Once you’ve reviewed your customer history, it’s now time to firm up on your buyer personas. What sort of people buy your products? Are there typical demographic factors that you need to take into account?
If you are a CRM provider, it’s not very valuable to focus all your energy on selling to a sales executive. Not only are they probably too junior to make buying decisions for their company, but it’s probably also not their area of expertise.
In this case, it’s probably best to immediately disqualify the lead — they’re never going to buy, so you’re just wasting your time pursuing them. Just because that particular prospect is not the right fit for your company, doesn’t mean you want to disqualify the entire company, so you might hunt down someone that has a more targeted job title, or a better fit for you. For example, if you see a CMO engaging with your brand, s/he should probably receive more attention from your marketing team.
Location is another key demographic factor. Say you’re a B2C company that sells handmade shoes to Europe and North America — this means that you can easily disqualify any prospects who are based in Asia, Africa, or elsewhere.
Whilst these examples are overly simplistic, the takeaways are the same across lead qualifications models. They’re the key things that you need to be thinking about when defining who constitutes an MQL. Just because someone shows an interest in your company doesn’t mean that they’re your ideal customer.
While it can sometimes feel painful to disqualify a “lead”, it’ll save you time and hassle further down the line.
3) Speak to your sales team
Make sure you receive as much feedback as possible from your sales team. Who do they find easiest to sell to? Why? And who’s hardest to sell to?
Your sales team directly interacts with your company’s prospects every day, so they have a wealth of invaluable insights that you should take on board. Marketing and sales shouldn’t lock horns or see each other as competition — instead, they need to facilitate one another.
Ask your sales team to make a conscious effort to glean feedback from each and every prospect. How did they come across your company? What in particular made them want to purchase your goods? How did your company differentiate itself from the competition?
As well as giving you feedback from the prospects themselves, your sales team will also give you feedback on their experience interacting with them.
After all, it’s marketing’s job to enable sales to help them close more deals. Ask your sales team if there are any content pieces they need that might help them. White papers, email templates, call scripts, data sheets, etc. are all tools marketing can deliver to help sales win more.
One common problem is that MQLs are qualified as SQLs too early on in the funnel. While this may make the marketing team feel good, if these prospects aren’t yet ready to purchase then it’s pointless.
By pitching too hard, too early, you may well end up putting the customer off — and damaging the company’s bottom line in the process.
4) Tinker away
Defining an MQL is an ongoing process — if the sales team is ever unhappy with the leads they’re being given, then that means you’ve incorrectly qualified them.
It’s unlikely that you get the qualifying criteria spot on the first time around. However, the more you learn about your customers’ buying journey, the tighter you can make your target personas. The more feedback you get from your sales team, the closer you’ll come to hitting the mark.
Why is it so important to define MQLs?
Correct lead qualification will save your organization time, make your marketing efforts more productive, and ultimately improve your bottom line by converting more prospects into customers.
Lead qualification ought to occur very early on the pipeline. By doing this as soon as a new lead comes in, you can quickly work out whether they’re worth your attention (i.e. qualifiable) or if they’re unlikely to ever purchase.
Plus, qualifying at the beginning stage of the buyer’s journey is a great way to personalize your marketing and sales approach. Not all leads are created equal — for example, if you have a really hot lead come in then you’re better off passing them over to sales sooner rather than later.
Likewise, you don’t want to adopt a hard sales approach if a prospect is only slightly interested in your company.
How many SQLs come through each week without first having been MQLs? How many potential customers sign up for a demo or get in touch directly with a sales representative?
For most businesses, this number is pretty low. However, many more people are still interested in your products — but they just aren’t yet ready to purchase. Maybe they’ve been on your website, clicked through on a few of your ads, but are still unsure about your offerings.
In these instances, you don’t want to scare off prospects by treating them like true SQLs. There’s nothing more annoying than being bombarded constantly with sales emails from a company that you haven’t even bought from yet.
By immediately identifying them as MQLs as soon as they come in, you can start to plan a more subtle approach to converting them.
In short, without properly identifying MQLs, you’d end up wasting time and energy marketing to prospects who have no need or desire to purchase your product — or you’d prematurely send all prospects to your sales team (and risk putting them off). Perhaps more importantly, you’ll be creating an environment where sales does not value the leads that marketing is passing over.
How defining an MQL helps show ROI
Certain aspects of marketing — such as brand awareness and brand reputation — rest on intangible metrics. It’s hard to assess awareness and reputation, so you’re left second-guessing the ROI of your efforts.
When marketers identify MQLs, however, it gives them a tangible metric (and goal) on which to judge their efforts.
For example, the marketing team might be given a budget of $1 million for a single quarter. Their performance for that period will then be assessed on both the number of MQLs they generate with that budget, and the percentage of MQLs that become SQLs.
When it comes to the next quarter, the marketing team’s budget going forward will depend on the ROI of their efforts to date.
This obviously isn’t the whole story. Perhaps only a small number of leads that you passed over to sales become customers and so you need to tinker with your definition of an MQL.
However, having a solid definition of what success looks like is critical. What does an MQL look like? And at what stage of the funnel should they then become an SQL?
How many MQLs does your organization need to generate?
There’s no simple answer to this — it totally depends on your industry, the quality of your products, the competition, and the skill of your sales team. In essence, you need to create enough MQLs to turn into SQLs, which sales will then hopefully turn into customers.
To work this figure out, look at your historic conversion rate between MQLs and SQLs. Then, look at the drop-off rate between SQLs and customers. Whilst you should always be refining your processes in order to reduce the number of drop-offs, this historic ratio should give you a good idea as to how many MQLs you need to generate.
Remember, though, that this will require continuous work and tinkering on your part — if the sales team is having difficulty converting MQLs that have been passed over to them as SQLs, then you need to change your MQL criteria. As with all things digital marketing, it’s a constantly evolving process.
More than 60% of Google’s search engine traffic came from mobile devices through the first six months of 2019, as more and more consumers moved their online purchasing journeys from desktop to mobile.
For small business owners and digital marketers, call-only ads and call extensions are effective ways to capitalize on this trend, improve mobile conversion rates, and drive sales by reaching potential customers further into the sales funnel.
So how do you do that for your business? To begin with, let’s go over the basics.
What is a call-only ad?
Call-only ads are a type of search ad that only display on devices that can make phone calls. These ads appear above or below the organic search results when a user enters a query with a search term you’ve won at auction.
When a user clicks on a call-only ad, their mobile device automatically dials the phone number to your business—all they have to do is tap the send button to make the call. This happens no matter where on the ad the user clicks.
Call-only ads include your phone number, the name of your business, a display-only URL, and a brief description of your business. Some optional ad extensions can also be added.
What’s the difference between call-only ads vs call extensions?
Call-only ads only do one thing, no matter where the user clicks: dial the number to your business. Text ads with call extensions may do a variety of different things in addition to dialing your number, depending on where you click.
Both call-only ads and text ads can include ad extensions. Ad extensions are optional components you can include in your ad to communicate additional information.
Call extensions are a specific type of ad extension that can be included as part of a text ad.
The text ad may be configured to display on both desktop and mobile devices, but the call extension will only show up when the ad is being displayed on call-enabled devices.
Text ads always include a headline, a short description of your business, and a display URL; every text ad contains at least one component that links to a landing page somewhere on the web. Like call-only ads, when a user clicks on a call extension, the dialer on their device opens up and dials the number to your business. They must hit send to initiate the call.
The key difference here is that call extensions are not the only place on the ad that a user can click. If a user clicks the headline, for instance, they’ll be linked to your website. If you’ve got a location extension in the ad, they can click your address, which might open Google maps.
In contrast, Call-only ads do only and exactly what you’d expect: calls are the only action a user can take.
Why call campaigns?
Calls, as a type of interaction, are more valuable than clicks or impressions, and are likewise more expensive. Unlike the cost-per-click (CPC) or cost-per-mille (CPM) models that are common metrics when bidding for text and display ads, you’ll be bidding on the value of a phone call for calls-only campaigns. What makes them more valuable and why does it make sense to lay out the extra dough for calls?
For one thing, calls-only ads remove the leakiest part of the conversion funnel.
The conversion funnel for desktop users goes like this: view ad > click ad > arrive at landing page > lead captured. The third step of that flow—when users reach your website—is the point at which you’re most likely to lose people, according to WordStream.
Call-only ads remove that step all together and create a shorter, more efficient conversion funnel: view ad > call business > lead captured.
Choosing between call-only ads vs call extensions
While phone calls are more valuable than website traffic in a vacuum, every marketing decision should be made within the context of individual campaigns. And like any tactic in your campaign toolbox, call-only ads and call extensions should be deployed in ways that best align with your business goals.
Call extensions are useful for when you want to make it easy for people to call you, but you’d like to give them the opportunity to visit your website as well. Call-only ads are best used when your highest priority is getting people on the phone.
Here are two examples that highlight the difference.
Case Study #1: Call extensions
Let’s say you’re marketing a restaurant that specializes in cheese sandwiches. You’ve decided to bid on the search term “best cheese sandwiches near me,” and you’ve won your auction, so your ad will enjoy premium placement above organic cheese sandwich search results.
You know that 81% of smartphone owners use their devices to find restaurants, so you’ve decided to display your search ads on mobile. You want to attract customers, and calls convert at a higher rate. However, you choose to run a text ad with a call extension instead of a calls-only ad. Why?
Phone calls are good for business, and you want people who are ready to order to be able to skip your landing page and dial right away. However, the margins in the cheese sandwich biz are thinner than a sliver of parmesan on a caesar salad, and you don’t have much staff to field phone calls.
To minimize the time your employees spend taking phone orders, you’d like people to know what they want before they call, perhaps by visiting your website to check out your menu. In fact, you’ve recently set up an online ordering system that makes your business run more efficiently than ever, and even though you still value phone calls, your ideal world would be one in which every customer orders online. In this case, text ads with call extensions are a Gouda idea.
Case Study #2: Call-only ads
In our second example, your business sells life insurance (you never know when one might choke on a cheese sandwich). You know that people usually spend a lot of time researching online before making a purchase decision, and you want to target users that are further into the conversion funnel, once they’ve narrowed down their choices. Furthermore, getting and keeping people on the phone is the least difficult inbound sales task. You target a keyword you think will attract the right audience, win the auction, and choose a calls-only campaign.
Your customers have a lot of specific, personal questions they want answered before pulling the trigger on a policy, the type of questions that are complicated and difficult to answer on a website. Given that what you’re selling is a significant, long-term investment, people generally want personal treatment. Plus, you’ve got a large, well-trained, and motivated sales team (they work on commission, after all), who are terrific at closing the deal once they get a potential customer on the line.
Rather than risk leaking away leads from your landing page, your main goal is to get people on the phone with an agent. In this case, a calls-only ad would insure that you’re optimizing your mobile conversion rates.
Creating a call extension
- Select the dropdown arrow of the Extensions tab and choose Call extensions
- Select the + Call extensions button and enter properties for the call extension
- Select which Campaigns and Ad Groups you want to display the call extension
Creating a call-only ad
- In your Google Ads account, click Ads & Extensions
- Click Ads, then select the + button
- Select Call-only ad
- Click Select an ad group and choose which ad group you want
From here, enter the following for your call-only ad:
- Two headlines (optional, but recommended)
- Your business name and phone number (required)
- Two descriptions (the second description is optional)
- Your display URL and verification URL (optional)
How to set up calls-only ads for success
Google offers a complete guide for setting up a calls-only campaign. Follow the tips below to fully leverage your calls-only ads and optimize your mobile conversion rate.
1. Set up advanced call tracking
Call tracking is a critical component to the success of your mobile call campaigns, but Google’s built-in option only provides basic information like area code and call duration. Advanced call tracking with CallRail drills deep, allowing you to determine which keywords are driving calls, which calls are leading to sales, and even how much each call is worth.
2. Prepare your staff
Make sure staff are prepared to field calls driven by your call campaign. Create selling points and conversation tips, and instruct everyone on how to properly route calls. CallRail’s call tracking also allows agents to rate the quality of a call by pressing a number after the user hangs up.
3. Write strong description copy and A/B test it
Unlike text ads, call-only ads don’t have a headline—just the name of your business, a phone number, and an 80-character description. Make sure you use those 80 characters wisely; be concise and clear about what you offer and try to include a call to action. Set up A/B testing to see which are most effective at generating clicks.
4. Run ads during business hours
Make sure your business is open and someone is available to answer the phone to get the most value out of call conversions. Consider where the customer is in their purchasing journey and what actions they are ready to take.
The post Call campaign tactics: Call-only ads vs call extensions appeared first on CallRail.
Great leaders listen. They understand the importance of keeping their ears – and a line of communication – open when it comes to their teams. With channel partners, modern tools like PRM platforms make it simple to continuously monitor KPIs. But there’s nothing like a good, old-fashioned survey to net honest and straight-from-the-horse’s-mouth opinions from partners. That’s why they’re still an invaluable tool for measuring partner satisfaction, one you should be using consistently and effectively.
Surveys 101: where to start
How do you best administer a survey? Keep the KISS principle in mind. That stands for Keep It Simple, Stupid. You’re going to get the best results from a survey when the questions are simple and easy to understand.
A busy partner is going to be discouraged by surveys too frequent, complicated or lengthy. Be respectful of their time and keep surveys to-the-point and easy to answer. There’s a reason why clickable 1-5 scale or agree/disagree-type answers are so popular: they’re simple and quick. Use them, when appropriate. Fillable text answer fields are necessary for some questions, but be strategic with their use because they’re time-consuming. Another absolute must: make survey responses anonymous. You’re much more likely to get honest – and thus, insightful – responses.
The million dollar question(s)
When you’re formulating survey questions, ask about but don’t limit yourself to the obvious – the bottom line. A satisfaction survey should also shed light on whether you’re succeeding in building strong, cooperative and open relationships with your partners, and if you’re providing them the tools they need to find success. Daunted? Don’t be. We’ve got you covered with some subjects to consider touching on, and possible questions to ask for each.
1. Profitability. How profitable are we to work for?
2. Quality of product/service. Do you believe in the quality of our product/service? Are you proud to sell our product/service?
3. Measuring churn. Are you, or have you ever thought about, selling for our competitors? How likely are you to be still selling our product/service a year from now?
4. Customer feedback. How often do you receive customer feedback? Is customer feedback usually positive or negative? What feedback have you received about our product/service from your customers?
5. Resources. Do we offer a sufficient number of partner resources? How easy are resources to find? How easy is it to understand how to use them? What hurdles prevent you from using partner resources?
6. Training and learning. Do we provide all the learning resources you need? How effective is our training format? What’s the biggest hurdle when it comes to completing training and learning tracks?
7. Marketing. How effective are the sales and marketing materials we provide? Do you understand how to use them?
8. Support. When you reach out to us, how helpful is our support team? How easy it is to get in touch? What are the barriers to reaching out? Do you feel listened to when you contact us?
9. Engagement. Do you feel like a valued member of our team? How often are you using our partner portal? Do you feel that you know what’s going on at our company? Do you understand our strategies and goals?
10. Give them the microphone. If you could change one thing about our partner program, what would it be? Do you have any ideas you’d like to pass along to us? Is there anything else you’d like to share?
When the survey’s done, your work has just begun
The wealth of information you’ve collected shouldn’t be shoved in a corner to collect dust. Use it! Are there things that survey results indicate you’re doing right? That’s great – continue with the good work. Are there some rough patches revealed by partner responses? Use the intel to strategize how you’ll go about smoothing them. Want to really be an open book? Share the results with partners, not shying away from not-so-flattering results and asking for input on a correction. Chances are, they’re already aware of areas of shortcoming and may have some useful ideas for improvement. It’s a great opportunity to promote openness and collaboration.
One last thing to consider: don’t look at surveys as islands unto themselves. They’re just a snapshot in time. Comparing a survey’s results to past ones will shed light on trends and help you see if the process paths you’re taking to improve are the right ones. Real leaders listen but they also know that success rests on constant improvement, and surveys are an important tool in that.
The post Writing a partner satisfaction survey? Here’s what to ask. appeared first on Partner Relationship Management Software (PRM).
This guest post was written by our friends at Edison21, a digital marketing agency that specializes in PPC advertising and reporting for Shopify store owners.
ROI (return on investment) is a surprisingly tricky metric to track and communicate in your digital marketing campaign. Proper ROI reporting shows if a digital campaign is working and a product or service is doing well, and whether it requires a few additional essential pieces to work correctly.
Before digital advertising, ROI was both easier — and harder — to prove.
For instance, buying a TV ad theoretically allowed access to a percentage of viewers, but Nielsen and their self-reported viewer tracking could only guess at how people many actually saw the ad run on TV. Still, this kind of reporting process was long accepted as the best way to understand TV ad campaign ROI.
With digital tracking this kind of guessing has been reduced, but not eliminated. Between the multiple platforms involved — Google Analytics, Google, Facebook, LinkedIn, Amazon, and eCommerce platforms — it can take expert-level analysis to not only determine ROI of each campaign and communicate those results simply to stakeholders.
Today, we’re going to cover four essential steps for ROI reporting for you or your clients:
- Establish clear goals for what you’re looking to accomplish with your digital campaigns
- Identify the formula you’ll use to calculate your return on investment
- Ensure accurate tracking is in place so progress to goals is measured accurately
- Customize reports based on the stakeholder and the type of decisions they’re looking to make with their data
First, let’s talk about goals
Before we get into the nitty-gritty of ROI reporting and tracking, it’s crucial to understand what (and why) you’re tracking at all.
Is your goal more online sales? Brand awareness? Greater social media followings? Lead generation form submissions? While any of those examples are suitable, they all have unique metrics and often are communicated under a different context.
These goals should be clearly stated in every report, ensuring clients see a clear progression over time. Keep it simple, keep it straightforward, and keep them separate — your clients will appreciate it.
Now let’s jump into the good stuff: Measuring, tracking, and reporting on ROI.
How do you measure ROI?
ROI is an important indicator of whether a campaign is generating the desired result.
For example, if an eCommerce company spends $1,000 on advertising and those campaigns generate $5,000 in sales, the campaign ROI is 5x their cost with 20% of total revenue going towards those ads.
If that 20% is lower than their margin, the company will have a profit. If not, they’ll be losing money on each sale.
ROI can be measured three main ways: the above, revenue minus advertising spend, is great for one-time purchases, but the simple equation often lacks all the additional expenses that come with a digital marketing campaign.
The second, calculated using customer acquisition cost (CAC) and customer lifetime value (CLV), works best for repeated purchases and subscriptions.
- The formula for CAC is marketing spend divided by the total number of new customers.
- CLV is calculated by multiplying average purchase value by purchase frequency to get average customer value (ACV) and then multiplying ACV by average customer lifespan.
- Finally, subtract CAC from CLV to get a great measure of how your business is doing or divide CLV by CAC to get your ad spend to customer lifetime value ratio.
For practice, let’s use Netflix as an example.
Netflix’s average monthly subscription price is $12.66 (add up each tier, divide by three). Let’s say Netflix is offering a free monthly trial and, for simplicity’s sake, ignore Netflix’s other marketing costs and plugin $12.66 as the CAC. After that, let’s assume Netflix churn rate (monthly customer loss) is a steady 5 percent.
A monthly churn rate of 5 percent tells us a customer typically stays with Netflix for 20 months (1 / churn rate = customer lifetime). $12.66 per month for 20 months gives us a customer lifetime value of $253.20. Divide the CLV by CAC for a ratio of 20:1, or subtract $12.66 from $253.20 to get a lifetime revenue of $240.54.
While Netflix clearly does not have a 20:1 ad spend to lifetime revenue ratio (remember, we didn’t add in their monthly marketing/advertising budgets), you can see how these numbers work to tell a story on the effectiveness of campaigns.
Many digital campaigns look for returns around 4:1 or 5:1, but we’ve seen higher and lower depending on the business.
The last kind of analysis, and the one most often used on digital projects or campaigns, is simply the first equation with more expenses included.
In sum, comprehensive ROI reporting and tracking for a campaign requires labor or agency costs, ad spend, online subscription services, and other marketing costs.
Measuring ROI progress starts with good processes
We’ve established our goals and how we will measure ROI, so now it’s onto creating the process for measuring success.
ROI tracking isn’t useful unless all the data is accurately tracked, so that’s where we begin.
First, we determine which areas need tracking. Conversions should be based on your business and goals. Form submissions? Yup. Phone calls? Yes again. Purchases? You betcha. Ad clicks? Pageviews? Both helpful, but less so than more solid leads or actual customer conversions.
Next, your PPC or marketing agency needs to set up your conversion tracking based on your goals and check that conversions are firing when they’re supposed to.
Conversion pixels, the code that records conversions, will track client actions throughout the sales funnel, making it far simpler to keep track of customer touchpoints.
Now you can accurately track prospects when they interact with your brand and complete the desired goals which is absolutely critical to start showing ROI.
Building the perfect report
After ensuring all data is being tracked correctly, the next step in ROI tracking is using a platform that aggregates data from multiple sources.
There are lots of different platforms involved in PPC reporting — Google ads, Facebook ads, eCommerce platform reporting, to name a few — and they all pull data in different ways.
We’ve found NinjaCat to be a useful tool as it allows agencies to holistically examine data by pulling from wherever your efforts touch. Need Facebook clicks, Instagram views, and Google analytics all in one place so you can see how your campaign is fairing across each channel? Want to compare clicks of views across different websites or web apps? NinjaCat allows users to slice and dice data any way you need it. (Plus it integrates nicely with CallRail!)
If you’re not ready to purchase an expensive reporting software, CallRail offers form tracking, call tracking, and integration with the major ad platforms to start monitoring ROI between your various ad platforms. It’s a great place to start.
Comparing results from Google ads to Facebook ads can show patterns that may not be visible on one platform alone, or could highlight when Google sees a drop in traffic while Facebook spikes.
Having the ability to track lead forms and phone calls alongside ad traffic — which CallRail is built to do — gives agencies and their clients the ability to see more than just clicks and page views. The power to see real business interactions turn into qualified leads and sales is what this is all about.
After ensuring data is tracked correctly and choosing a platform to aggregate that data, it’s time to pull out interesting insights.
When building a report for client stakeholders, make sure you start with data that’s valuable for them, both short and long term. Remember that senior-level people are looking to talk returns and bigger trends (months maybe years, not days and weeks), instead of impressions, clicks, and other low-level data more useful to internal marketing and advertising teams. Thinking macro, not micro, will allow the data to tell a story far beyond the raw numbers.
Snapshot views are quite helpful — think one-page spreadsheets with key metrics highlighted; sales funnel visualizations with numbers, and even country comparisons depending on the client. Stick with summaries and main data points — stakeholders want valuable data but too much can overwhelm. Examples include:
- 90-day baseline reports showing historical performance next to benchmarks which provide a roadmap for future optimizations
- Monthly check-in reports displaying plan improvements for the following month along with any shifts in priorities or budgets that can impact PPC campaigns
- Quarterly and/or annual reports taking into account seasonality trends, news or economic event effects, and industry shifts while reflecting back on monthly optimizations and baseline objectives.
Customizing reports depending on business types is also key. For example, eCommerce and lead generation reports may share some marketing and/or advertising assets, but because overall goals and data are different, each requires its own approach.
eCommerce is cut and dry: The main goal in conversion tracking here is to ensure proper attribution across sites or digital marketing/advertising campaigns. Care should be taken to compare data from different sources — what Shopify is saying was sold versus what Google Analytics has tracked — to best understand what is being tracked correctly and what isn’t. Attribution is the goal here, using multiple methods to track such gives a thorough idea of what’s working well.
Lead generation is more subjective, as the focus can often lean more on the quality of leads. While linking leads to sources is certainly helpful for future campaigns, the health of any good lead gen campaign is often better determined by the close rates of leads obtained. Good companies will have at least a loose set of guidelines describing what makes a lead good and track all close rates down to a purchase.
While ROI tracking isn’t the sole indicator of a company’s marketing campaign, it’s a critical indicator for ad budgeting to show profitability and gauge results.