Programmatic buying is sometimes a complicated topic, but DR THOMAS OOSTHUIZEN, Global Consulting Director at Acceleration UK, breaks it down into ten easy to follow steps.
The most important issue when dealing with programmatic buying is to be aware of algorithm bias. As data sources and points grow, this problem will decrease. But in most statistical techniques, the most salient data points often dominate and will continue to do so. We have to design to avoid this.
Pure common sense will tell us that as long as some marketers have more resources than others, “average” algorithms will benefit the large and jeopardise the small. This means that, even in algorithms, creative thinking is important. One size will not fit all.
Here are some tips to ensure maximum benefit from data-based algorithmically driven buying:
1. Know your product or service category
We need to understand whether our category is growing fast, maturing or declining? Different conditions and requirements come into being once a category develops from a fast-growing initial phase into a mature condition.
2. Is the market saturated?
In a saturated market we need to look for niche segments that will enable wider expansion? To do so, we need to find out who these consumers are. Once we have done so, we need to understand how to expand the algorithm to enable us to identify and target them.
3. If growing, differentiation is less important.
However, if the segment or category is not growing differentiation is key. We need to discover what are the signals that will enable the algorithm to detect these variations. Without this, our brand will simply fall into the trap of algorithm “same-ness”, where less is, in fact, less.
4. Is our brand a leader or a challenger?
Leading brands can leverage all the economies they can access. However, smaller brands need to work far harder at being different.
5. Is our brand properly differentiated?
If so, how? This may include features, benefits, emotions, personality types, symbols, words, statements, slogans, colours, iconography and communities. It’s clear that a small brand will have a vastly different profile than a smaller one. Hence, using the same algorithms a large brand uses is simply a waste of money. We then need to build in bias our differentiation “bias” so that it becomes a focused tool.
6. Are results declining over time?
If so, why? Can a changed algorithm assist or does the problem lie outside of that? It’s always tempting to constantly adjust algorithms, but we need to be aware that the problem may be something completely unrelated. Keeping an open mind is crucial when working at a granular level.
7. Can we segment algorithm groups?
If so, can we learn more about what separates algorithms that are greater or lesser predictors of sales results? Understanding how they explain a category is very useful, particularly when this is a significant factor in planning exposure.
8. Can we build in “bias”?
Our algorithms need to contain enough granularity that we are able to fine-tune them to match whatever it is that differentiates us. By following trendsetters or up-weighting data from groups that demonstrate differences we can build this necessary “bias” into our algorithms.
9. Can we test different options and assess results?
This is usually resource-dependent. The fewer resources we have, the more we will have to rely on testing to provide the data we need.
10. Can we expand diversity?
If so, will the incrementally deeper and more creative messaging give us an above average return on investment?
This is by no means an exhaustive checklist, but by applying these tips we will be able to apply our programmatic buying algorithms more effectively.
Stop being creepy! An essential guide for digital marketers
Advertising and marketing is becoming increasingly creepy as personalisation strategies lose the plot, writes JOAN OSTERLOH, authorised Forrester Research Partner for South Africa.
Marketers need to be aware of the “creep factor” when deploying strategies of personalisation and individualisation in their marketing efforts, Forrester’s Brendan Witcher, VP and principal analyst serving eBusiness and channel strategy professionals, warned as early as December 2017.
Six months later, Forrester senior analyst Susan Bidel was even more direct in her message: “Marketers, you need to take control of your advertising strategies and adtech stacks now to better address today’s consumers.” She cautioned that those who didn’t, were at a high risk of annoying and creeping out the very customers needed for business growth.
In its latest research, “Marketers Versus Customers: Opposing Forces Erupt” Forrester now finds that even though marketers set out with the best intentions to implement customer-obsessed marketing and customer experience strategies, they still end up alienating and ‘creeping out’ customers, resulting in lost loyalty.
Marketers use personalisation to make their marketing more relevant and to help it stand out, Forrester says in a blog on the study. The irony is that with all the customer data that marketers use to personalise, the one thing they seem to have forgotten to find out from consumers is whether they even want personalised communication at all, the firm writes. Combined with identity resolution and increased automation, companies have created adtech and martech stacks that are creeping people out. We think our phones are listening to us. And then Facebook admits it is doing this. So, what’s gone wrong?
The report by Melissa Parrish, Forrester’s VP and group director serving marketing professionals, highlights that marketers are ignoring their customers’ desire for anonymity, by assuming that they all want personalised experiences. They are foregoing the authenticity of their own brands by “giving lip service to brand values they think resonate with customers.” There’s an overt focus on martech at the expense of human creativity. Lastly, they’re profiling customers on precarious connections and getting it wrong, sometimes with harmful and even traumatic results, she explains.
The solution is to return to true customer-centricity by going back to basics by looking at the following, Parrish writes in the report:
- Remember that customers are different. Here it’s not about customer segments or personas, but rather the extent to which they expect you to know them. Treat customers and prospects differently – e.g. prospects “want value, not a background check”.
- Customers are tired of lookalike ads and direct mail that is poorly personalised, trying to get them to buy things for which they’re not even in the market. Choose your target audience, focus on them, and then let go of the others.
- Programmatic marketing has its upsides and downsides. Avoid the two extremes of advertising at scale across multiple channels on the one hand and limiting advertising to channels where everyone seems to be at once, such as Facebook, on the other. Instead, target your audience with responsible content and choose platforms on which you can reach them online and offline.
- Consider whether you should be using cookie, key-stroke and audience data at all for your brand. Intent-based target marketing through search optimization might be a smarter choice.
- Don’t assume that personalisation will make customer experiences more relevant. Rather interview your customers and test different variations of personalised content to find the right balance between information, recommendations, simplicity and empathy.
- Don’t ignore the 20% who don’t want any personalisation at all – use your customer insights data to identify them, and then meet their expectation of no personalisation.
Parrish offers important recommendations for the winning marketers of the future. Since the success of marketing is measured by the bottom line of revenue generation, truly customer-obsessed marketers need KPIs that are “fine-tuned” to understand what customers value, not what’s valuable to the brand, she writes. What customers want and value should be defined in terms of four dimensions along the axes of functional-experiential, and economic-symbolic. Then, measure the dimensions along the entire customer life cycle, she explains. What this requires is the following:
Firstly, marketing and Customer Experience (CX) teams need to unify and leverage one another’s unique skills to deliver best-in-class customer experiences that drive loyalty, customer retention and growth. Truly customer-obsessed brands will bring CX and marketing together to harness the best that both have to offer.
Secondly, brands need to rebuild trust. As consumers become more privacy-savvy, they will become more selective about the brands with which they are willing to share their data. Marketers need to develop ‘Privacy Personas’ as a new marketing segment to ensure that they deliver experiences their customers are comfortable with.
Thirdly, refocus on creative excellence. In Parrish’s words “new prospecting strategies will center on great creative making an emotional impact and contextual targeting driving relevance.”
Lastly marketers need to find ways to extend customer obsession throughout the enterprise. Employees need to be empowered to deliver on the brand promise, which must align to and be in harmony with CX. The companies that thrive will be those whose CX truly reflects brand values, Parrish concludes.
Sources: “Marketers Versus Customers: Opposing Forces Erupt” 18 Sept 2019. By Melissa Parrish with Sharyn Leaver, Brigitte Majewski, Caroline Robertson, and Stephanie Liu.
Which should you use: PIN or Password?
By CHAD HAMMOND, a digital security expert at NordPass
As users of this digital age, we have many different choices. You can enable or disable web cookies, depending on how much information you want a website to gather about you. You can use encrypted services or unencrypted ones, depending on how much you’re concerned about your privacy and security.
You can also use a PIN (Personal Identification Number) or password to secure your digital devices or online accounts. However, in this particular case, the choice for most of us is not as straightforward as it seems.
The other day I also had the very same discussion among my friends with three different sides of opinion. One side was backing PINs and claiming that they are safer than passwords. Others couldn’t believe that PINs made up of four, six, or eight digits can be more reliable than long and complex passwords. And the third group was claiming that both PIN and password serve the same purpose of identification and are safe to use. All sides had valuable insights, but we couldn’t reach an agreement. Sparked by this discussion, I decided to look deeper into this topic and look for the truth.
When should you use a PIN?
PIN stands for a Personal Information Number and is used the same as a password to prove that you have the right to access your data. A PIN usually consists of a string of four to eight numbers, and it was first introduced in the 1960s together with cash machines (ATMs). The obvious drawback is that a PIN is limited to 0-9 numerical digits. A PIN made up of four numbers offers 10,000 possible combinations. That may seem like an easy nut to crack, but it’s not as straightforward.
PINs are normally used on touchscreen devices and always require manual data entry. An automated brute-force attack may not work as most of the systems that use a PIN also specify maximum attempts count before disabling the device.
For example, if your device limits PIN entry to six attempts, there is a 0.06% chance that someone will be lucky enough to crack the four-digit code. Of course, if your PIN is ‘0000’ or ‘1234,’ the probability of being hacked increases massively.
When should you use a password?
A good password is a combination of numerical digits, upper- and lowercase letters, and various special characters. It could also be a phrase made up of words with the same requirements. Like the PIN, the password concept first appeared in the early 1960s and has been used ever since. A 10-character password has 59,873,693,923,837,900,000 different variations, and most of you are probably thinking you know which of the two is more secure. However, it’s not all about mathematics.
Passwords are used online or for devices like computers, which usually don’t have any limits on failed attempts. That’s why passwords can be compromised with the help of an automated brute-force attack. Of course, not all attacks are practical, as most of them would take years to crack a strong password. Buthacking technologies are evolving fast, making such attacks more sophisticated and successful.
Password vs. PIN: the verdict
Going back to the discussion that I had with my friends, we can safely say that all the opinions were correct in one way or another. The answer to this question depends on where you use your PIN or password.
If you want to unlock your touchscreen device, the safest and easiest way is to use a PIN because of the manual entry and the attempt limit. When it comes to online accounts or computers, passwords are much safer due to the simple math of available combinations.
Also, you can enable multi-factor authentication (2FA) in most online accounts . The 2FA adds another layer of safety, minimizing the risks of automated brute-force attacks. Even if someone manages to get your strong password, they won’t be able to access your account, as the second step of verification will stop them.