Understanding the impact of your marketing activity
As a society, we seem to have a fascination with measurement. We love to measure things, know the results, and track our progress. In our personal lives, we use smartwatches to measure the steps we take, our sleep patterns, manage fitness routines, and track our GPS location. At work, we set goals and schedule performance reviews to measure our progress towards achieving them. We mentally compare ourselves against others all the time and are even said to "take the measure of a man" when assessing their character. Measurement helps us to understand where we are in relation to where we want to be, so we can hopefully formulate a plan to move to the next step.
In marketing, we have taken the idea of measurement to a whole new level, with an ever-increasing focus on the field of analytics. There is an old saying that, "I know half of my advertising 'doesn't work; I just 'don't know which half." Although its origins are a bit unclear, it is attributed most often to John Wanamaker, a U.S. merchant who was considered to be somewhat of a marketing pioneer.
We have gone from that "half" truth to trying to decipher each bit of activity and attach a meaning to it. Marketing has become more complex and sophisticated in the digital age, and we do need to know whether it is having an impact or not. We must, however, go about this process of melding marketing and analytics with a defined effort that produces useful information, not just to get data, but to use that data to make meaningful improvements for our customers.
The Increased Complexities of Digital Marketing
Attribution has always been a challenge, with it being difficult to explain what finally motivated the consumer to purchase. Focus groups evolved to judge targets' reactions to particular advertisements, A/B testing allowed us to measure one iteration against another, and complex formulas were developed to calculate the Return on Investment (ROI) of each campaign element.
Just as marketers seemed to have a solid understanding for gauging how a change in their activities could result in increased lead generation, prospect engagement and customer acquisition, along came digital to turn everything on its head. The online world was supposed to be the big equaliser – any company could promote its product or service cost-effectively and generate impressive results which could be measured instantaneously. All you had to do was get on board and get moving! However, it turned out to be more complicated than that.
Instead of making marketing easier, digital seems to have added layers of complexity. With a plethora of marketing and communication opportunities now available and the focus on omnichannel strategies, it is more challenging to know what impact any one element of a campaign has on the prospective consumer. Data analysis is more important than ever for shining the spotlight on what works and why.
Never Forget: The Consumer is Still King (or Queen)
The most important for marketers to remember is that it is not about them at all. In the end, it is still about the consumer. As advertisers, we can promote how great the product is, or how excellent our company is, but that does not matter unless the end consumer sees something in it that speaks to his or her needs.
As marketers, we can brag all we want about our ability to track leads and measure results, but we must still remember that it is the actions of actual people we are following. It is essential to customers that you demonstrate an understanding of their relationship and behaviour with you. They want to know that you genuinely understand and care about their needs and motivations, and that they are not just a number in a database that you cleverly manipulate to achieve a sale. In the end, understanding our customers better through measurement and analysis needs to be motivated by a desire to refine the customer experience and deliver the information they’ll find relevant and useful.
Martech Is The Reality Of Modern Marketing
"Beware of letting the tail wag the dog: technology is integral to modern marketing, but tools are no replacement for strategy."
~ Author Colin Lewis in an opinion column for Marketing Week, "A 'Marketer's View of Martech."
Due to the consumer's enthusiastic adoption of digital communications, marketing today has evolved a suite of tools described as marketing technology, or martech. Nevertheless, figuring out exactly which portion of a digital marketing campaign caused a tipping point in the buying process is still a significant challenge for marketers and requires sophisticated marketing campaign analytics.
Marketing automation platforms allow companies to create exceptional customer experiences and personalised buyer journeys at scale. They can be used to create content, schedule it, actively target communications, respond to interactions, maintain lists, and manage relationships with ease. The real-world marketing applications of martech now mean:
Instant Action: Marketers can gather information on target customers in real-time. They can form instant customer profiles, segment them, and target individuals for specific messaging.
More Personalisation: Identifying a target persona means individualised content that resonates with each lead can be created and delivered.
Broader Reach: It is easier than ever to deliver coordinated campaigns across multiple digital channels such as social media, email and personalised landing pages.
Better Analytics: Marketing automation analytics and social marketing analytics can be used to help peer into the future to predict what actions consumers might take in reaction to specific activities.
Cost Information: Martech enables a more informed understanding of cost-per-acquisition from each marketing channel.
Automation: Many activities can now be automated so that we can implement marketing campaigns at precisely the right moment for maximum effectiveness.
Measurement in Action
"What gets measured gets managed."
― Pearl Zhu, Digital Maturity: Take a Journey of a Thousand Miles from Functioning to Delight
Marketing attribution is the science of identifying events that led to the desired outcome of a call, click-through, in-person visit, or form completion. These analytics might include:
Email Analytics: Email remains a cornerstone component of digital marketing, so its success should be tracked right through to bottom-line ROI. Marketing managers and decision-makers need to know whether an email message was bounced or delivered, whether it was opened and read, and which link the recipient used to click-through to a landing page. These analytics will allow for message analysis and optimisation.
Campaign Tracking: Campaigns need to be followed end-to-end to understand conversion cost and ROI. Marketing analytics track conversions from an initial website visit through an expression of interest and meaningful engagement, through the final sale.
Google AdWords Integration: Many marketers use Google AdWords to capture attention on search engine result pages. Analytics can be used to see which keywords performed most effectively and track costs through from interest to sale.
Behaviour Tracking Analytics: These provide data to help better understand lead interactions from website visits, emails, webinars and social media so that automation can continue to provide the engagement necessary to move the prospect along in their unique buying process.
Social Marketing Analytics: Understand the behaviour of prospects concerning social media engagements on Facebook, Twitter, Instagram, LinkedIn, YouTube and other digital communication opportunities.
KPIs For Digital Marketing
Key Performance Indicators (KPIs) are used to evaluate the success of particular marketing activities. They enable the marketing team to make better and more informed decisions moving forward. To create KPIs, you need to
Establish your goals and objectives.
Understand the critical success factors underpinning those goals.
Delineate the key performance indicators associated with those success factors.
Collect the necessary measurement data.
Calculate results from the raw data, analyse it, and make decisions about actions moving forward.
When calculating the impact of marketing activity, appropriate KPIs might include:
Digital Analytics KPIs
Creating specific digital marketing KPIs helps marketers determine targets and goals and measure the performance of digital marketing efforts based on those values. Typical digital marketing KPIs might include:
Source of website traffic
Increased brand awareness on social media
Search engine effectiveness
Cost per lead
Number of new and returning website visitors
Website page interactions
Online lead conversion rates
Click-through rates
Lifetime value of a customer relationship
Lead Generation KPIs
Since many forms of digital marketing can be used to generate leads, multiple KPIs can be used to track lead generation effectiveness, including:
Conversions from the lead generation source to the next step
Bounce rate from email campaigns
Average website session duration
Lost lead
Revenue generated
Return on Investment
Organic traffic generated
Return on PPC ad spend
Lead acquisition cost
Lead value
Lead attribution channel
Marketing Analytics KPIs
These are the specific metrics that define progress towards meeting set goals within the digital marketing campaign to make adjustments and maximise ROI, including:
Overall cost per lead generated
Overall digital marketing campaign ROI
Sales revenue generated
Average sales cycle
Lifetime revenue
ROI for inbound marketing and outbound marketing
Social media interaction, conversion and ROI metrics
New lead generation
Lead to customer conversion
General and personalised landing page conversion rates
Organic traffic generated and converted
Mobile site lead generation, conversion and ROI metrics
Digital marketing is continuously evolving and increasingly complex, but it can be both manageable and enjoyable! 1827 Marketing handles all of the functions necessary to simplify and streamline marketing activities that make an impact.
The latest innovation in AI technology is context-aware tools, which enable businesses to design custom environments for their AI partners. This shift from prompt engineering to context design promises to transform how organisations manage and leverage their knowledge.