Google Ads Auto-Applied Recommendations Are Terrible
Carlton Hoyt
Unfortunately, Google has attempted to make them ubiquitous.
Google Ads has been rapidly expanding their use of auto-applied recommendations recently, to the point where it briefly became my least favorite thing until I turned almost all auto-apply recommendations off for all the Google Ads accounts which we manage.
Google Ads has a long history of thinking it’s smarter than you and failing. Left unchecked, its “optimization” strategies have the potential to drain your advertising budgets and destroy your advertising ROI. Many users of Google Ads’ product ads should be familiar with this. Product ads don’t allow you to set targeting, and instead Google chooses the targeting based on the content on the product page. That, by itself, is fine. The problem is when Google tries to maximize its ROI and looks to expand the targeting contextually. To give a practical example of this, we were managing an account advertising rotary evaporators. Rotary evaporators are very commonly used in the cannabis industry, so sometimes people would search for rotary evaporator related terms along with cannabis terms. Google “learned” that cannabis-related terms were relevant to rotary evaporators: a downward spiral which eventually led to Google showing this account’s product ads for searches such as “expensive bongs.” Most people looking for expensive bongs probably saw a rotary evaporator, didn’t know what it was but did see it was expensive, and clicked on it out of curiosity. Google took that cue as rotary evaporators being relevant for searches for “expensive bongs” and then continued to expand outwards from there. The end result was us having to continuously play negative keyword whack-a-mole to try to exclude all the increasingly irrelevant terms that Google thought were relevant to rotary evaporators because the ads were still getting clicks. Over time, this devolved into Google expanding the rotary evaporator product ads to searches for – and this is not a joke – “crack pipes”.
The moral of that story, which is not about auto-applied recommendations, is that Google does not understand complex products and services such as those in the life sciences. It likewise does not understand the complexities and nuances of individual life science businesses. It paints in broad strokes, because broad strokes are easier to code, the managers don’t care because their changes make Google money, and considering Google has something of a monopoly it has very little incentive to improve its services because almost no one is going to pull their advertising dollars from the company which has about 90% of search volume excluding China. Having had some time to see the changes which Google’s auto-apply recommendations make, you can see the implicit assumptions which got built in. Google either thinks you are selling something like pizza or legal services and largely have no clue what you’re doing, or that you have a highly developed marketing program with holistic, integrated analytics.
As an example of the damage that Google’s auto-applied recommendations can do, take a CRO we are working with. Like many CROs, they offer services across a number of different indications. They have different ad groups for different indications. After Google had auto-applied some recommendations, some of which were bidding-related, we ended up with ad groups which had over 100x difference in cost per click. In an ad group with highly specific and targeted keywords, there is no reasonable argument for how Google could possibly optimize in a way which, in the process of optimizing for conversions, it decided one ad group should have a CPC more than 100x that of another. The optimizations did not lead to more conversions, either.
Google’s “AI” ad account optimizer further decided to optimize a display ad campaign for the same client by changing bidding from manual CPC to optimizing for conversions. The campaign went from getting about 1800 clicks / week at a cost of about $30, to getting 96 clicks per week at a cost of $46. CPC went from $0.02 to $0.48! No wonder they wanted to change the bidding; they showed the ads 70x less (CTR was not materially different before / after Google’s auto-applied recommendations) and charged 24x more. Note that the targeting did not change. What Google was optimizing for was their own revenue per impression! It’s the same thing they’re doing when they decide to show rotary evaporator product ads on searches for crack pipes.
Furthermore, Google’s optimizations to the ads themselves amount to horribly generic guesswork. A common optimization is to simply include the name of the ad group or terms from pieces of the destination URL in ad copy. GPT-3 would be horrified at the illiteracy of Google Ads’ optimization “AI”.
A Select Few Auto-Apply Recommendations Are Worth Leaving On
Google has a total of 23 recommendation types. Of those, I always leave on:
- Use optimized ad rotation. There is very little opportunity for this to cause harm, and it addresses a point difficult to determine on your own: what ads will work best at what time. Just let Google figure this out. There isn’t any potential for misaligned incentives here.
- Expand your reach with Google search partners. I always have this on anyway. It’s just more traffic. Unless you’re particularly concerned about the quality of traffic from sites which aren’t google.com, there’s no reason to turn this off.
- Upgrade your conversion tracking. This allows for more nuanced conversion attribution, and is generally a good idea.
A whole 3/24. Some others are situationally useful, however:
- Add responsive search ads can be useful if you’re having problems with quality score and your ad relevance is stated as being “below average”. This will, generally, allow Google to generate new ad copy that it thinks is relevant. Be warned, Google is very bad at generating ad copy. It will frequently keyword spam without regard to context, but at least you’ll see what it wants to you to do to generate more “relevant” ads. Note that I suggest this over “improve your responsive search ads” such that Google doesn’t destroy the existing ad copy which you may have spent time and effort creating.
- Remove redundant keywords / remove non-serving keywords. Google says that these options will make your account easier to manage, and that is generally true. I usually have these off because if I have a redundant keyword it is usually for a good reason and non-serving keywords may become serving keywords occasionally if volume improves for a period of time, but if your goal is simplicity over deeper data and capturing every possible impression, then leave these on.
That’s all. I would recommend leaving the other 18 off at all times. Unless you are truly desperate and at a complete loss for ways to grow your traffic, you should never allow Google to expand your targeting. That lesson has been repeatedly learned with Product Ads over the past decade plus. Furthermore, do not let Google change your bidding. Your bidding methodology is likely a very intentional decision based on the nature of your sales cycle and your marketing and analytics infrastructure. This is not a situation where best practices are broadly applicable, but best practices are exactly what Google will try to enforce.
If you really don’t want to be bothered at all, just turn them all off. You won’t be missing much, and you’re probably saving yourself some headaches down the line. From our experience thus far, it seems that the ability of Google Ads’ optimization AI to help optimize Google Ads campaigns for life sciences companies is far lesser than its ability to create mayhem.
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Why People Are Loyal … to ANYTHING
Carlton Hoyt
I was reading the MarketingCharts newsletter today and saw a headline: “What Brings Website Visitors Back for More?” The data was based on a survey of 1000 people, and they found the top 4 reasons were, in order:
1) They find it valuable
2) It’s easy to use
3) There is no better alternative for the function it serves
4) They like it’s mission / vision
I thought about it for a second and had a realization – this is why people are loyal to ANYTHING! And achieving these 4 things should be precisely our goal as marketers:
1) Clearly demonstrate value
2) Make your offerings – and your marketing – accessible
3) Show why your particular thing is the best. (Hint: If it’s not the best you probably need to refine your positioning to find the market segment that it is the best for.)
4) Tell your audiences WHY. Get them to buy into it. Don’t just drone on about the what, but sell them on an idea. Captivate them with a belief!
Do those 4 things well, you win.
BTW, the MarketingCharts newsletter is a really good, easy to digest newsletter – mostly B2C focused but there’s some great stuff in there even for a B2B audience and you can get most of the key points in each day’s newsletter under a minute.
Are You Providing Self-Service Journeys?
Carlton Hoyt
Customers are owning more of their own decisions.
We’ve all heard the data on how customers are delaying contact with salespeople and owning more of their own decision journeys. Recent research from Forrester predicts that the share of B2B sales, by dollar value, conducted via e-commerce will increase by about a third from 2015 to 2020: from 9.3% to 12.1%. Why does Forrester see this number growing at such a rate? Primarily due to “channel-shifting B2B buyers” – people that are willfully conducting purchases entirely online rather than going through a manned sales channel.
All this adds up to more control of the journey residing with the customers themselves and less opportunities for salespeople to influence them. Your marketing needs to accommodate these control-desiring customers. It needs to accommodate as much of the buying journey as it can, and in many instances it can and should accommodate the entire buying journey – digitally.
Accommodating Digital Buying Journeys
Planning for the enablement of self-service journeys is a complex, multi-step process. In brief, it consists of:
- Understanding the relevant customer personas. Defining customer personas is always a somewhat ambiguous task, but my advice to those doing it is always not to over-define them. It’s easy to achieve so much granularity that the process of defining a customer persona becomes meaningless due to the presence of far too many personas with far too little to distinguish their journeys in a practical sense. It’s okay to paint with a broad brush. For a relatively small industry such as ours, factors such as “level of influence on the purchasing decision” and “familiarity with the technology” are far better than the commonly used definitions of B2C demographics which you’ll likely see used if you look up examples of creating customer personas. It probably doesn’t much matter if the scientist you’re defining is a millennial or Gen X-er, nor do you likely need to account for the difference between scientists and senior scientists. That’s not what’s important. Focus on the critical factors, and clear your mind of everything else.
- Mapping the journey for each persona. This can be done with data analytics, market research, and / or simply as a good old-fashioned thought experiment, depending on your resources and capabilities as well as how accurate you need to be. If you’re using data, use the customers who converted as examples and trace their buying journeys from the beginning (which will probably have online and offline components). Bin them each into the appropriate persona then use them to inform what the journey requires for each persona. The market research approach is fairly straightforward and can be done with any combination of interviews, focus groups, and user testing approaches. If you’re on a budget and just want to sit down and brainstorm out the decision journey, start with each “raw” customer persona, then ask “where does this person want to go next in his decision journey?” A scientist may want more information, they may desire a certain experience, etc. Continue asking that question until you get to the point of purchase.
- Mapping information or experiences to each step of the journey. Once you know the layout of the journeys and the goals at each step, it should be relatively clear what you need to provide the customer at each step to get them to move forward in their journey. This step is really just asking: “How will we address their needs at each discrete step of their journey?”
- Determine the most appropriate channel for the delivery of each experience. You now know what you’re going to deliver to each customer at each point in the decision journey to keep them moving forward, but how you deliver it is important as well. On paper, it might seem as though you can simply provide all the information and experiences the customer needs in one sitting and then that’s all they will need to complete their decision journey. In practice, it often doesn’t work that way. Decisions often involve multiple stakeholders and often take place over the course of days, weeks, or months. Few B2B life science purchasing decisions are conducted on impulse. For young or less familiar brands you may also need time for the scientist to develop sufficient familiarity with the brand in order to be comfortable purchasing from you. This is the time where you must consider not only the structure of the buying journey, but the somewhat less tangible elements of its progression. Structured correctly, your roadmap should essentially remove steps from the buying journey for the customer.
- Implement it! You now know what the scientists’ decision journeys look like and exactly how you’ll address them. Bring that knowledge into the real world and create a holistic digital experience that enables completion of the self-serve buying journey!
That’s it! Your marketing is now ready for today’s (and tomorrow’s) digitally-inclined buyers.
Owning the Journey
What we’ve outlined above will create a digital experience that allows customers to complete a purchasing decision on their own terms, which is something they increasingly want to do. If you build such an experience you will give yourself a definite advantage, but your customers will still shop around. It’s not enough to get them to hone in solely on your brand (which, if we’re being honest, is an incredibly difficult task).
Digital marketing is not only capable of enabling your scientist-customers to complete their decision journeys on their own, however. It is possible to create a digital experience that owns a hugely disproportionate share of the decision journey to provide outsized influence upon it. Such mechanisms are called decision engines, and when properly implemented they provide their creators with massive influence on their markets. If you would like to learn more about decision engines, check out this recent podcast we did on the topic with Life Science Marketing Radio or download our report on the topic.
Principal Consultant Carlton Hoyt recently sat down with Chris Conner for the Life Science Marketing Radio podcast to talk about decision engines, how they are transforming purchasing decisions, and what the implications are for life science marketers. The recording and transcript are below.
Transcript
CHRIS: Hello and welcome back. Thank you so much for joining us again today. Today we’re going to talk about decision engines. These are a way to help ease your customer’s buying process when there are multiple options to consider. So we’re going to talk about why that’s important and the considerations around deploying them. So if you offer lots and lots of products and customers have choices to make about the right ones, you don’t want to miss this episode.
(more…)
Personalization Can Backfire
Carlton Hoyt
Marketers are used to seeing a lot of data showing that improving personalization leads to improved demand generation. The more you tailor your message to the customer, the more relevant that message will be and the more likely the customer will choose your solution. Sounds reasonable, right?
In most cases personalization is great, but what those aforementioned studies and all the “10,000-foot view” data misses is that there are a subset of customers for whom personalization doesn’t help. There are times when personalization can actually hurt you.
When Personalization Backfires
Stressing the points which are most important to an individual works great … when that individual has sole responsibility for the purchasing decision. For large or complex purchases, however, that is often not the case. When different individuals involved in a purchasing decision have different priorities and are receiving different messages tailored to their individual needs, personalization can act as a catalyst for divergence within the group, leading different members to reinforce their own needs and prevent consensus-building.
Marketers are poor at addressing the problems in group purchasing. A CEB study of 5000 B2B purchasers found that the likelihood of any purchase being made decreases dramatically as the size of the group making the decision increases; from an 81% likelihood of purchase for an individual, to just 31% for a group of six.
For group purchases, marketers need to focus less on personalization and more on creating consensus.
Building Consensus for Group Purchases
Personalization reinforces each individual’s perspective. In order to more effectively sell to groups, marketers need to reinforce shared perspectives of the problem and the solution. Highlight areas of common agreement. Use common language. Develop learning experiences which are relevant to the entire group and can be shared among them.
Personalization focuses on convincing individuals that your solution is the best. In order to better build consensus, equip individuals with the tools and information they need to provide perspective about the problem to their group. While most marketers spend their time pushing their solution, the CEB found that the sticking point in most groups is agreeing upon the nature of the solution that should be sought. By providing individuals within the groups who may favor your solution with the ability to frame the nature of the problem to others in their group, you’ll help those who have a nascent desire to advocate for you advocates get past this sticking point and guide the group to be receptive of your type of solution. Having helped them clear that critical barrier, you’ll be better positioned for the fight against solely your direct competitors.
Winning a sale requires more than just understanding the individual. We’ve been trained to believe that personalization is universally good, but that doesn’t align with reality. For group decisions, ensure your marketing isn’t reinforcing the individual, but rather building consensus within the group. Only then can you be reliably successful at not only overcoming competing companies, but overcoming the greatest alternative of all: a decision not to purchase anything.
The End Is Not Nigh (now let’s get serious…)
Carlton Hoyt
People love to decry the end of marketing. It’s a good attention-getter. While those who shout about the coming of the end of marketing from their soapboxes are usually guilty of lacking realism or using poor logic, they do make us think about the future and that can be a learning experience. Let’s take an example…
Knowledge @ Wharton recently published an interesting, albeit narrow-sighted and overly apocalyptic article about the end of marketing and what, according to the author, will be the very narrow opportunities to engage audiences that will remain in the future. The author does a very good job of identifying trends but a very bad job of predicting what the future will likely look like, but both the good and the bad provide important lessons and highlight valuable opportunities.
First, the trends. No reason to discuss these much because most should be more or less obvious to anyone reading this.
- People would rather listen to other people than brands.
- People are going to greater lengths to avoid the onslaught of advertisement.
- Marketing technology “cannot truly understand the complexities of consumer intent” and therefore hitting the trifecta of the right message on the right channel at the right time is exceedingly difficult. (This I would actually say is up for debate. It’s a gray area. A discussion for another time, perhaps…)
- Marketers are overwhelming digital channels, further driving users to avoid marketing out of simple necessity. See point #2.
And here are the author’s four corresponding points of how he envisions the future:
- “As consumers bypass media with greater ease, the social feed is the wormhole to the entire online experience.”
- “As consumers outcompete marketers for each other’s attention, every piece of media contained in the feed is not only shareable, but shoppable.” – basically, he’s arguing that social channels become capable of performing transactions.
- “As the individual controls the marketing experience, communication shifts from public to semi-private.” In other words, people move from things like Facebook to things like Snapchat, where there are fewer ads and more privacy.
- Only two types of marketing will remain: discounts / sales and transparent sponsored content.
These predictions amount to a wild fantasy.
The most obvious flaw in the author’s reasoning is that somehow a completely shoppable social media ecosystem would evade the rules that everyone else has to play by – namely that when marketing becomes overwhelming, the audience will block it out or leave. This also ignores the plain fact that the large majority of the things that people buy are not found organically via social media. There is no shortage of people who shop. Decisions may be influenced in the social sphere, and perhaps some impulse decisions both begin and end there, but those are the exception; the overwhelming majority of purchasing decisions do not occur entirely within the social sphere and that would not change if social channels were empowered with transactability.
The real world contains a great deal of equilibrium. The ability to target people and their ability to tune it out is a balancing act. It is a cat and mouse game. Technology works both ways, and as new channels and technologies are born there become more ways to reach customers. However, as channels are flooded, the impact of each individual effort diminishes. Marketing self-regulates by decreasing its own ROI as utilization of any particular channel increases.
So What Will the Future of Marketing Look Like?
There are definitely many channels that will continue their trend towards ineffectiveness. It’s increasingly likely that audiences, fed up with maddening digital display advertising techniques, continue to adopt ad blocking technology and erode the potential of that channel. Email, while still rated as a high-ROI channel, is looking like it may have a perilous future as email service providers become better at filtering out promotions. Social media will certainly take on a larger share of permission-based marketing, but it will remain a risky business to rely too much on “rented” audiences. Increasing utilization of content marketing will continue to add noise and, in turn, increase its own cost by requiring better and better content to obtain the inherently limited resource it seeks to obtain: the audience’s attention. Increased use of social media may, if adoption increases as we project, fall victim to a similar effect, limiting brands’ ability to market effectively using social channels.
Not all developments will be bad. A decline in interruption tactics will lead to a fundamental shift in how marketing is viewed from a tool to generate demand to a mechanism to deliver value to audiences and a source of strategic advantage. Customer-centric resources and other owned platforms will proliferate as companies seek new ways to deliver value to customers while increasing the affinity level between customer and brand. These companies with strong brand affinities will create sustainable advantage for themselves as they shortcut and compress the customer decision journeys. Additionally, new and yet unknown channels will develop, and at increasingly rapid pace. Consider that until about 20 years ago, no digital channels existed at all. Accelerating technology development will continue this trend and also enable more personalized, coordinated, and targeted marketing in a manner which is more accessible and usable by companies of all sizes, budgets and capabilities.
I’m not going to try to pinpoint detailed specifics – I’m not claiming to be a psychic and it would be a waste of your time to read simple conjecture – but there are things that we can be fairly certain of given current trends, a bit of logic, and a hint of foresight. Marketing isn’t going anywhere, and while in the future it may not look quite like it does today, it will still be something that Philip Kotler would distinctly recognize.
Remove Steps With Content
Carlton Hoyt
While we strongly advocate that many content marketers in the life sciences shift from a content paradigm to a resource paradigm, there are still ample roles for more traditional content to play. This is especially true in demand generation endeavors when content is being leveraged to fulfill a specific role in a buying journey. When using content to move prospects closer to making a sale, the most effective content removes steps from the customers’ buying journeys. It actually makes the journey shorter while influencing the customer in a way that favors your brand.
If you want to create content that moves your scientist-customers forward in their buying journeys, you need to know where you’re starting, where they’ll finish, and not try to take a larger step than your content is able. To create great content that can help shorten a buying journey and direct customers in your favor, follow these 4 planning steps before actually putting pen to paper.
1) Map the buying journey.
You can’t effectively influence customers to progress in their buying journeys unless you understand the nature and the steps within those buying journeys. There is no shortcut to this – you need to talk to the customers. When doing so, it’s important to get feedback from a broad range of customers. In addition to simply speaking with different demographics (for instance, customers in different market sectors or those with varying seniority), it’s important to speak with those whose buying journeys have ended differently. Talk to your own customers, those who have made purchases of alternate or similar solutions, those currently involved in a purchasing decision, and some who have exited a buying journey without making a purchase. It’s important to understand all of the paths these journeys took and the factors that led to their ultimate decision.
Remember: a buying journey is not a line. It is a roadmap, where there are multiple routes from the start to the destination, and you want to understand those various routes as much as possible. Mapping the buying journey is something that will be useful well beyond content planning, so it’s a good thing to do regardless. For instance, a map of the customers’ buying journey is invaluable when designing campaigns. It’s not a simple or fast process, but it’s well worth the effort.
2) Pick a step to remove.
Once you understand the “routes” the buying journey may take, you can decide which step you want to remove. To be broadly effective and achieve the best ROI, this should be a step that is on many of the routes and is not presently being addressed well. It should also not be too large of a step, as there is a practical limitation to how much of the buying journey you can bypass with content.
3) Determine why that step exists.
The step you’re trying to remove is there for a reason. The scientist-customer may be trying to understand something, or seeking a particular experience, or looking to verify a specific belief. Unless you know exactly what they’re trying to do, you can’t design content to bypass that step.
In many cases you may be able to use your own best judgment to understand why a step in the buying journey exists, and in others you may want to speak to the target market. The more effort you put into this process the more likely you’ll end up with a correct answer, but the effort needs to be proportional to the effort required to actually create the content. Otherwise, you’d be just as well off taking the “shotgun” approach, designing a few different pieces of content, and A/B testing.
However, to know how much effort you would need to design the content, step 3 needs to overlap with step 4…
4) Determine the best way to bypass the step.
Churning out white papers is only going to get you so far, and there are a lot of steps in the buying journey that can only be effectively skipped by richer content. If your audience seeks only information, there may be a wide variety of content formats you can choose from. If your audience requires an experience, you may be required to use rich media.
The only way to use content to skip a step in the buying journey is to provide the audience with exactly what they are looking for. You can’t take a shortcut and expect to be effective.
There are far too many companies who use their content marketing programs haphazardly, as blog post and white paper factories. Those are wasted efforts. When creating content to generate demand, understand the buying journey, focus on a particular step, then design content to fulfill the needs of that step and get scientists past it. Only then will your content program achieve its potential.
Remarketing by the Numbers
Carlton Hoyt
We recently cited some newly released findings from the Boston Consulting Group (BCG) stating that “display retargeting from paid search ads can deliver a 40 percent reduction in CPA.” It was met with some hesitation from Mariano Guzmán of Laboratorios Conda, who stated:
“[…] when I have clicked on a [life science website] what I have experienced is a tremendous amount of retargeting for 1 month that I have not liked at all as an internet user, and I do not feel my clients would as well”
Being me, I like to answer questions with facts as much as possible, so I dug some up. This one’s for you, Mariano!
To directly address Mariano’s concern, I found some studies on people’s opinions on retargeting. A 2012 Pew Research Study found that 68% of people are “not okay with it” due to behavior tracking while 28% are “okay with it” because of more relevant ads and information (4% had no opinion). I’m a little skeptical of the Pew study because they were priming the audience with reasons to “be okay” or “not be okay” with remarketing. In a sense, these people are choosing between behavior tracking + more relevant ads vs. no behavior tracking + less relevant ads. However, when users actually see the ads the ads don’t say to the viewer “by the way, we’re tracking your behavior.” Are some users aware of this? Certainly. Might some think it consciously? On occasion, sure, but nowhere near 100% of the time. However, 100% of the Pew study respondents were aware of it.
A slightly more recent 2013 study commissioned by Androit Digital and performed by Toluna asked the qusestion in a much more neutral manner (see page three of the linked-to study). They found that 30% have a positive impression about a brand for which they see retargeting ads, only 11% have a negative impression, and 59% have a neutral impression.
The Pew study and the Androit Digital study did agree on one thing – remarketing ads get noticed. In both, almost 60% of respondents noticed ads that were related to previous sites visited or products viewed.
Now to the undeniably positive side… The gains a company stands to make from remarketing.
In addition to the 40% reduction in cost per action cited in the aforementioned BCG study, a 2014 report from BCG entitled “Adding Data, Boosting Impact: Improving Engagement and Performance in Digital Advertising” found that retargeting improves overall CPC by 10%.
A 2010 comScore study evaluated the change in branded search queries for different types of digital advertising and found retargeting had provided the largest increase: 1046%.
In a 2011 Wall Street Journal article, Sucharita Mulpuru, an analyst at Forrester Research, stated that retail conversion rates are 3% on PCs and 4% to 5% on tablets. According to the National Retail Federation, 8% of customers will return to make a purchase on their own. Retargeting increases that number more than three-fold, to 26%.
There are many more studies that sing the praises of remarketing, however I wanted to stay away from case studies that investigate only single companies as well as data collected and presented by advertising service providers.
Here are my thoughts on the matter: Do some customers view retargeting unfavorably? Certainly, but that’s the nature of advertising. No matter what form it takes, some people will object to it. Considering that there is nothing ethically wrong with retargeting, we can’t give up on something that is proven to be a highly effective tactic because some people have an objection to it. In the end, it’s our job as marketers to help create success for the organizations we serve.
Avoiding Skepticism
Carlton Hoyt
The scientific buying journey is fraught with skepticism. From the buyer’s perspective, this is a requirement of a good buying journey. The buyer must decide what to believe and what not to believe, determine what is meaningful and what is not, and refine their understanding of their own needs all while being blasted with marketing messages from companies that are all trying to get the scientist’s business. Skepticism is a natural and required component of these efforts. It is also the enemy of the marketer.
Skepticism is what makes overly pushy and overtly bombastic messages fail. It’s also part of the fuel for the rise in content marketing. Marketers are looking for ways to convey their messages in manners that create less skepticism. Rather than immediately jumping to validation, promotion, and flat-out selling, they first attempt to educate in a more subtly guiding manner which conditions the scientists to viewpoints that will be later elaborated on in the more traditional marketing efforts. However, promoting content to scientists is not the same as the scientists discovering content on their own, and the manner in which content is presented will, in part, determine their receptiveness to it. Additionally, taking a “hands off” approach throughout the buying journey such as to avoid skepticism would lead to overall marketing ineffectiveness due to low rates of opportunity development later in the journey.
Educational content is often necessary, but never sufficient. We therefore must consider the nature of messages, as well as how those messages are to be delivered, such that we can avoid skepticism-driven rejection earlier in the buying journey while still creating the desired effect in the later stages of the buying journey: a closed sale.
Evolving Message Types
Early in the journey, the customer is gathering information and may not even yet realize that they have a need for a product. At this stage, educational content is the way to go. You want to help them learn and discover information that will prime them to your point of view without giving them reason to be skeptical (as promoting a commercial solution would).
As they transition from discovery and exploration to analysis, they know a need exists and start to actively gather and evaluate options. Educational content is still useful, so long as it is focused on the customers’ needs. Basic background information is of little interest to the customer at this point, unless it is something so disruptive to their journey that they need to reconsider its premises. Additionally, we want to start adding validation content – content that demonstrates to them that the solution we are advocating is correct. (For example, case studies are a very common form of validation content.) This type of content will help them understand our offering as a qualified option to solve their need. If the customer has been properly educated to accept our point of view earlier in the buying journey, validation content will not raise skepticism.
As they come to the late stages of analysis and approach their buying decision, educational content should be largely avoided in favor of additional validation as well as promotions – the “hard sell,” as we call it. At this point the opportunity exists; we just need to seize it! Dancing around it with more educational content will not effectively prompt action. More direct calls to action are required.
Message Centricity
Let me lead off with this reminder: life science marketers should always maintain a focus on their scientist-customers. That said, customer-centricity exists on a sliding scale, as most things do, and is not absolute. Changing the centricity of your messages throughout the buying journey is also necessary for optimal performance.
Early in the journey, we should have a nearly exclusive customer focus. Everything should be framed from the perspective of the customer and their needs. We should adopt their perspective as much as possible. As the journey continues, we can shed a little bit of this customer-centricity, giving room to focus more first on the technology, then ultimately on the product. We are not shifting to a product-focus. We are shifting to a customer-centric product focus. We can never focus solely on the product. Why? The product is a lower-order need and our scientist-customers will respond vastly better to higher-order needs (the reason they need your solution in the first place).
Mechanism of Discovery
The manner in which messages are delivered can raise skepticism. However, the mechanisms that raise the least skepticism are not the most effective throughout the buying journey, so shifting mechanisms of message delivery / discovery must be considered as well.
Messages that are naturally found by your audience tend to raise far less skepticism than messages that are pushed upon them. Early in the buying journey, we want to rely on mechanisms that are organic – those which allow the messages or content to be found naturally by your audience or in a manner that feels natural. They should be able to actively choose to interact with it rather than have it pushed upon them. This could include organic search, display or native advertising, and placement within third party media. In general, marketing tactics that are considered inbound would roughly overlap with organic discovery. Regardless, the customer must feel as if they are driving their own discovery.
As the customer has more interaction with your brand and consents to receive marketing, you can begin to transition from pull to push. Even with permission, you should avoid the temptation to get too pushy too quickly, as you can still very easily raise skepticism by doing so. As the customer progresses through the buying journey, you can transition more from customer-driven discovery to a more visibly active role in leading them. This more active role will be necessary; if you were to always wait for the customer to “organically” discover and interact with your content, you could very well lose mindshare to your competitors. Therefore, a careful and evolving balance is required throughout the buying journey.
Transitioning Goals
While the ultimate goal of closing a sale remains the same throughout the buying journey, looking at the interim goals can help to understand both why the aforementioned transitions are necessary and how to execute them. In brief, we transition from:
- Shifting the scientists’ viewpoint without activating skepticism …
- … to convincing them that the adopted viewpoint is the correct one …
- … to persuading them to act on their beliefs and execute a transaction.
We shift from seeking to primarily avoid rejection as the customer remains open to many viewpoints, to seeking acceptance as the customer evaluates and filters their options towards an ultimate decision.
Avoiding skepticism is undeniably important, and raising skepticism with your marketing can shut your brand out of a customers’ buying journey early on. However, the approaches that we use to avoid skepticism do not make for an efficient marketing platform as the buying journey progresses. Many of the mechanisms that create skepticism are needed to close opportunities. By understanding where customers’ are in their buying journeys, and matching our approaches to it to create balance, we simultaneously limit skepticism while increasing the ultimate likelihood of a sale.
Guide to Win / Loss Analysis
Carlton Hoyt
As we discussed last week, there are only two fundamental reasons why someone won’t buy from you. Either you are talking to the wrong person, or the prospective customer doesn’t trust you. Unfortunately for commercial professionals, the reasons why someone could lack sufficient trust in you to purchase are myriad. Doubly unfortunately, those reasons often go undiscovered. Many organizations performing little analysis of why any given sale is won or lost, others do so superficially in ways that don’t provide meaningful information. Even more confusingly, many companies think they are performing win / loss analysis when really they aren’t! They are instead utilizing other tools and methods, often in an ad hoc and undocumented manner, which provide biased or misleading information!
Performing win / loss analysis correctly is not a trivial endeavor and requires a good deal of planning, but there are many benefits to doing so. These include:
- Clearer understanding of the customer buying journey
- Better understanding of the competition’s offerings (including pricing, positioning, etc.)
- Early identification of market trends
- Better understanding customer preferences
- Understanding how you and your competition are perceived
- A built-in “warning system” which informs you if your messaging is missing the mark
- Feedback on performance of the sales team and effectiveness of sales processes
- Market feedback to help guide product development
Planning for Win / Loss Analysis
Remember that win / loss analysis is a form of market research. It requires proper planning – and adherence to the plans – to ensure that the execution yields the answers you’re looking for.
The first question that needs to be answered is: who will implement the program? This should not be your sales organization! Ideally, the people running the program and performing the interviews will be far removed from the sales process. An external agency who is familiar with your market and experienced in performing win / loss analysis would be ideal, however other internal departments or functions can be used (usually a market research or CI person / team, if you have one, otherwise the applicable product manager or another relevant marketing person would be a good choice to head the effort).
Next, decide what specific objectives you hope to achieve from the win / loss analysis. There are basics that are central to the reasons a sale is won or lost and will therefore almost always be included, such as understanding the customers’ decision criteria and knowing how you measured up against the competition across a number of key factors, but you will also have the opportunity to obtain a plethora of other information. For the sake of customer participation and limiting the cost and / or effort, you will be limited to how much additional information you’ll be able to collect. You will therefore need to determine what non-core information is the most important. Are you interested in learning more about your competitors’ offerings? Do you want to know more specifics about the customers’ buying journeys? Are you interested in the finer details of how your brand is perceived compared to the competition? For long, consultative sales a customer may be more willing to engage with you in a lengthy interview. For short, low-value purchases where sales interaction was limited or non-existent, you probably won’t find customers willing to sit through a long interview. Know what can be realistically expected from your audience and plan accordingly.
The next question you need to answer is: what opportunities will be analyzed? Given the time and / or cost required to perform win / loss analysis, it is often only applied to major product lines or service areas and / or large accounts. (We do not recommend only analyzing large accounts unless your focus is improving win rate solely to large accounts; if you want to improve the win rate for all customer classes, you need to analyze them all.) You can define which opportunities will be analyzed more narrowly to cut down on the number of interviews and amount of analysis necessary, or you can be more broad to collect information about more opportunities and then perform post-hoc analyses of specific products, markets, etc. You also need to determine the frequency at which opportunities that meet the defined criteria will be analyzed. If the nature of your business is such that you have a low number of high-value opportunities, you may want to analyze them all. If you have a high number of low-value opportunities you may want to analyze only some of them. If you will be analyzing only some, you should select them either at random or at regular intervals (for example, at the conclusion of every fourth opportunity, chronologically) to prevent bias. Furthermore, ensure your criteria don’t exclude wins! It’s just as important to understand why you win as why you lose, and understanding your wins can be even more informative.
From the defined objectives, plan your questionnaire. There are a massive number of potential questions, and if you’ve clearly laid out your objectives the questions you need to ask should become somewhat obvious, but here are a few common ones to get you started:
- What caused you to initially consider a purchase of this type?
- Which other companies / products / solutions were being considered? Which one was ultimately chosen?
- What actions on the part of our team made notable positive or negative impressions?
- What selection criteria was used to make the ultimate decision?
- What interaction influenced you most during your decision-making process?
- How did our pricing compare to the competition?
- Why did / didn’t we win your business?
- Who was involved in the purchase decision?
- Were you comfortable with the product features / company’s capabilities? Which were most / least important?
- How do you perceive our company? How do you perceive our competitors?
- Would you be likely to recommend our solution to others?
A common issue with win / loss analysis questionnaires is the tendency to focus almost exclusively on the latter stages of the buying journey. Remember that the early stages of the buying journey are often more influential. Ensure you ask questions that will inform you how well you are setting the stage for a win, as many lost opportunities aren’t simply failures to close.
If you end up wanting to ask more questions than they reasonably can, remember that not every interview needs to ask the same questions. If you feel that a question has been sufficiently answered, change it out and ask another which would provide more new knowledge. You can also have multiple sets of questions and rotate through them to collect input, albeit less of it, on a larger number of some ancillary questions of lesser importance. (We strongly recommend always asking a set of “core” questions which directly address the most influential reasons for winning or losing.) If you ultimately want to ask more questions than would be feasible in an interview, you can create an accompanying questionnaire to collect additional data. This can be particularly useful if you wish to collect sizeable amounts of quantitative data which can be easily collected via an online survey or similar tool. Just remember that everything you ask a customer to do effectively has a conversion rate. Asking your customer to do two things will invariably lead to an increased number of incomplete data sets from respondents who either did not take / complete the interview but completed the questionnaire or vice versa.
Preparing for the Interview
Determine who will conduct the interview. Similarly to choosing the person or team to run the program, it’s best if the interviewer is not on the sales team. The interviewer should never be someone who was involved in the sales process for that particular customer. That consideration aside, the interviewer should be someone who is familiar with the product or service being sold, familiar with the market, understands the sales process without being too intimate with the sales team, and will make the respondent feel comfortable with the interview process.
Interviews should be scheduled with the customer or prospect very soon after the opportunity has ended. A good rule of thumb is that if more than a month has passed since the opportunity was closed or lost, don’t conduct an interview. Details of their decision journey and interactions with various companies need to be fresh on their minds in order to obtain accurate information, and collecting inaccurate information is often worse than collecting no information at all. When scheduling the interview, let them know exactly what to expect and what topics you are going to discuss. If there were multiple people involved in the prospect’s decision, they should be interviewed separately as they may have differing opinions and these differences can be stark at times. If you interview them collectively, you run the risk of those differing opinions not being expressed or falling victim to groupthink.
Before the interview, the interviewer should sit down with the sales team / person who was handling the opportunity and document some facts and perspective regarding the opportunity. How did the opportunity arise? Was there any previous relationship with the prospect? What tactics and sales tools were they using and why? Were there any noteworthy challenges during the process? What was the result and was it anticipated?
Performing the Interview
Interviews are generally performed by phone, although analogous communication tools such as teleconference can be used. In-person interviews can be performed as well so long as the customer is local and the interview can be performed without becoming cost-prohibitive. Being able to see the interviewee an be helpful, as gestures and body language can convey feelings which can in turn be used to help guide the conversation. (The interviewer’s impressions obtained from body language should not be documented as it could introduce a large degree of subjectivity. Additionally, when performing win / loss analysis across cultural borders, body language could be misread due to cultural differences.)
Any expectations of confidentiality should be discussed up front. As some purchasing processes involve sensitive information, ensure the interviewee(s) feel comfortable using any information necessary to fully explain themselves while knowing that any confidential information will not be recorded or shared.
The interview should have a “script” to ensure the interviewer asks all the questions, although some of which will likely vary slightly interview-to-interview (in phrasing or approach, not in intent) based on the nature of the opportunity and how the interview progresses. However, the questions on the script should be taken to be a minimum of the questions that need to be answered. A good interviewer will probe the interviewee to uncover the underlying reasons behind their answers. Simply surveying the interviewee by asking a set list of questions in sequence is a waste of a live interview and a good way to end up with incomplete information that is difficult to understand and / or leaves a lot of opportunity for guesswork. The ability to be meaningfully spontaneous is dependent on the interviewer’s knowledge of the market, the product bring sold, and the details of the opportunity and sales process for that specific prospect.
Post-Interview Analysis and Assimilation of Knowledge
Soon after each interview, send the customer a message to thank them. As with any customer interaction, a win / loss analysis is a branded experience and you want to ensure the customer experience is a good one in order to earn future business and cultivate brand advocates.
There is no single, correct way to analyze the information from a win / loss analysis because the information, and the kind of information collected, will vary based on the questions you are trying to answer and potentially other factors as well (as discussed earlier). However, data analysis provides ample opportunity to derail your win / loss analysis. It’s likely that most of your data is qualitative. If your organization has a tendency to be political, various groups may try to influence how the data is analyzed or presented in order to make themselves look better or further their own ends. It’s the job of the person managing the program to ensure this does not happen. Any quantitative data should be handled using proper statistics, and qualitative data should be analyzed in a way that is logical, defensible, and allows you to extract the necessary insight. Applying semi-quantitative methods to the analysis of qualitative data may help, but you shouldn’t limit yourself to them. Whatever methods you use to analyze the data, you need to ensure that they are consistent!
Once the data is distilled into knowledge, you need to ensure that it is utilized! When there is enough analyzed information to answer at least some of the questions that you defined in your objectives, a report should be drawn up and a meeting called with people from all departments who would stand to benefit from the resulting knowledge. (Depending on your company policies and culture, the reports and analysis may also be made available to anyone in the company who cares to learn from it, or restricted on a need-to-know basis.) At this meeting, the data and analysis are discussed, lessons learned are shared, and ideas can be generated for ways to improve – these ideas are the foundation for change. The results should inform your sales processes, market segmentation, product development, messaging, marketing communications, sales collateral, and other areas.
If you’ve obtained answers to some secondary objectives, you can remove the associated questions from the interview script. These may be replaced with questions to fulfill other knowledge objectives. Remember, however, that the primary purpose of win / loss analysis is to understand why you win or lose business! The core questions facilitating the answer to that question should, under most circumstances, not be removed or replaced. If you find yourself desiring the answer to other questions more than the answer to why you are winning / losing business, then you should use a different tool or approach which is more suited for the information you seek to gain. You may, however, rotate through other product lines or service categories in order to obtain information specific to other areas.
Closing Remarks
A recent Gartner study (“Tech Go-to-Market: Three Ways Marketers Can Use Data From Win/Loss Analysis to Increase Win Rates and Revenue“) found that less than one third of organizations conduct win / loss analysis properly. The same study found that win / loss analysis can increase win rates by as much as 50%! That should be no surprise. Understanding is the foundation upon which improvement must be built. Sure, win / loss analyses require a good deal of rigor and effort, but that 50% should be well worth it.