HeDe kans is groot dat de wereld binnenkort niet alleen wordt bevolkt door miljarden mensen, maar ook door miljarden robots. De IT-industrie wordt het terrein voor bedrijven die programma's ontwikkelen voor deze robots. Net zoals de nu voor menselijke gebruikers ontwikkelde apps zullen deze 'robo-apps' te downloaden en te installeren zijn.

De grenzen tussen robots en mensen vervagen. Bij transplantaties wordt gebruik gemaakt van elektronisch gestuurde kunstmatige organen en protheses. Nanorobots dringen diep in het lichaam door om medicijnen af te leveren bij zieke cellen of om microchirurgie uit te voeren. Speciaal geïnstalleerde houden toezicht op de gezondheid van mensen.

Mensen in slimme huizen wonen, waar het meeste comfort volledig is geautomatiseerd. De software waarop het huis draait regelt het verbruik en de aanvulling van energie, water, voedsel en andere voorzieningen.

Onze digitale alter ego's komen eindelijk volledig tot wasdom binnen een enkele, wereldwijde infrastructuur die in staat is tot zelfregulering en betrokken is bij het beheer van het leven op de planeet. Het systeem zal een beetje werken als het hedendaagse TOR; de meest actieve en effectieve gebruikers zullen moderatorrechten verdienen.

Niet alleen saaie klusjes behoren tot het verleden – ook de productie van bepaalde artikelen zal niet langer nodig zijn. In plaats daarvan stellen 3D-printers ons in staat alles te ontwerpen en te maken wat we nodig hebben.

De pc stond weliswaar aan de basis van de hele IT-revolutie, maar in 2045 zien we hem waarschijnlijk alleen nog in musea. De dingen om ons heen verwerken hun eigen informatie.

Niet iedereen zal even enthousiast zijn over die mooie, nieuwe robotwereld. Waarschijnlijk zullen technofoben in opstand komen om zich te verzetten tegen de ontwikkeling van intelligente huizen, geautomatiseerde levensstijlen en robots.

Bron: Automatiseringsgids, 22 Januari 2014

Data conscious consumers: What about them and how to target them?

Data is big news these days. Tech behemoths like Google and Facebook make a lot of money from our data, and people are growing increasingly aware of how valuable their data is to companies of all sizes.

But as data becomes increasingly valuable for companies, consumers are starting to question how much data they are prepared to give away. Many people are becoming uncomfortable with the idea of giving away their personal information.

It’s easy to understand their concerns. Huge data breaches each the headlines on a regular basis. It seems like every week, a large and respected brand loses millions of passwords or credit card details.

As consumers become warier about handing over their data, this poses a challenge for brands. How can you persuade your customers that it’s in their interests to hand over their data? And how can you market to them more effectively as a result?

Focus on the value exchange

If a consumer sees little value in handing over their data, they will be far less likely to do so. As such, your focus should be on trading data for something of value.

This idea has been around for a long time. Every time you sign up for an email list in return for a voucher or free eBook, this is the value exchange at work. Some companies use the concept of gated content whereby the consumer is given access to valuable content on a website in return for their data.

One of the most common ways that companies use this value exchange is to provide a better experience for the consumer in return for their data. In this case, the consumer may provide an app with permission to access their location, and the app then provides them with directions or specific products based on where they are.

In short, value exchange needs to be evident in some form. You need to convince your customers that they will enjoy a better experience or receive something of value in return for their data.

Understand different types of data consciousness

Consumers are all different, and they have different ideas about how their data should be used. Some consumers are perfectly happy to hand over their data, while others hold the opposite view.

Brands need to understand the differences between consumers before they can start marketing to them effectively. Consumers can broadly be separated into three groups:

1. Data unconcerned:These consumers do not care how their data is used and they are happy to hand over more data more readily.

2. Data pragmatists: These consumers are more guarded about their data, but they are willing to give it away if they can see a clear value exchange.

3. Data fundamentalists: These consumers are not willing to give away their data under any circumstances.

According to research from the Data & Marketing Association (DMA), the percentages of the population in each group are roughly as follows:

• Data unconcerned: 25%
• Data pragmatists: 50%
• Data fundamentalists: 25%

Clearly, when it comes to your marketing efforts, you want to be targeting those consumers in the 75% of the population under the ‘Data Unconcerned’ and ‘Data Pragmatists’ groups.

So how should you do this? There are three key principles to focus on.

1. Hyper-Personalization

Personalization has long been an important concept in marketing. But these days, businesses need to go beyond basic information like the consumer’s name and location. The focus should be on hyper-personalization.

Hyper-personalization uses data like browsing behavior, purchasing behavior and real-time data to change the message you send to your customers.

The first thing you will need to do is collect the data. You need quality data to personalize effectively, and that means you need to know the types of people who buy specific products, how much they spend, the types of models they are interested in, which brands they like, and more. Look at Spotify’s annual ‘Wrapped’ campaign, where the company sends users an annual roundup of their yearly listening. At first sight it’s a fun, quirky way to see user data in action. But it also shows exactly which data is being collected.

Context also comes into it. Factors like location, the weather, important events, seasons and real-time pricing can all be used in your messaging.

You could launch a browser abandonment campaign where you target people who were looking at a product but did not make a purchase, perhaps offering them a discount if they buy it now.

In short, the more personalized you can make your messaging, the more effective it will be.

2. Convenience

Other than personalization, businesses also need to focus on the convenience of your messaging. The hyper personalized communications need to be delivered through the right channels at the right times.

This means gathering data about the engagement techniques that work best for different types of consumers, and then using these to provide greater convenience for them.

3. Relevance

With all this collecting of data, there is a genuine concern that your business will annoy your customers and they will opt out of your communications.

As a result, it is necessary be careful about how data is gathered and how consumers are contacted. Data conscious consumers will have strict preferences about how they want to be communicated with. This preference data is essential to avoid alienating them.

By setting up a preference center where customers are asked how they want to communicate and the types of messages they want to receive. This can be done at the sign-up stage or later if preferred, perhaps by sending an email requesting the information.

Brands must also work to clarify the value of signing up to a service. If you can’t explain why you want their details, you shouldn’t have them. Use the Abercrombie & Fitch app for inspiration. Users who download it are rewarded with points that can add up to substantial discounts, and there’s a clear correlation between performing an action (i.e. registering) and receiving a gift.

Give consumers the option to opt-out of communications as well. Consumers may decide they don’t want your weekly newsletter, but rather than unsubscribing from all your communications, they may want to keep the promotions. Having the option to choose different types of emails they want to receive can be helpful in this case.

By managing customers’ data preferences effectively, businesses can ensure the right messages get to them more often.

Gather data and use it wisely

Marketing is changing all the time. Customers are more data conscious than ever, and this shows no signs of changing. To reach the right people with the right messages at the right time, you need to focus on gathering as much data as possible, without annoying your customers, and understanding your customers’ preferences.

That way, you can continue to reach them with (hyper-) personalizedand marketing messages that generate sales for your company.

Author: Jason Lark

Source: Dataversity

Suggesting that the digital marketing landscape has grown complex and fragmented is like saying that the universe is vast beyond description. Nobody (save for the astronomer, anyway) will argue with you. Truth is, sometimes considering the range of available digital marketing technologies can feel a bit like appraising infinite stars against an inky midnight sky. It can be overwhelming in its magnitude.

What you really need is a map:

But while the map may bring order to the madness, you still need a center of gravity, not unlike a galaxy or a solar system. In this more earth-bound context, the center of gravity is the digital marketing hub:

 Think of the digital marketing hub as an interstellar junction, the connection point between content, data, rules and insights that inform the next best offer or experience delivered across virtually any channel.

“Digital marketing hub” is the term that Gartner has adopted with the hope of disambiguating what so many vendors had come to ambiguously call “marketing clouds.” (Cloud, in our view, is a delivery option and an implementation detail, a hazy collection of droplets without any discernable form or focus. That’s hardly a description of any set of marketing applications or capabilities and, thus, hardly helpful as a naming convention. I’ve yet to hear anyone disagree, including the vendors themselves).

The digital marketing hub is the gravitational center to a constellation of digital marketing tools and applications. Specifically, the digital marketing hub converges around four fundamental capabilities:

1. A master audience profile—which unifies first- and third-party customer and audience data for targeting the right experiences to known customers and anonymous
2. Workflow and collaboration—which facilitates and streamlines the creation and onboarding of content, data, plans and other digital marketing assets and artifacts that feed the beast.
3. Intelligent orchestration—which informs the timing, targeting and coordination of content, offers and experiences across channels through a combination of business rules and algorithms.
4. Measurement and optimization—which traces the thread between marketing investments and business outcomes and allows marketers to optimize their budgets and efforts to highest yield.

This is all easier said than done, of course. Which is why we believe, more often than not, a digital marketing hub is a design pattern rather than something you buy off the shelf. The digital marketing hub, too, has its own center of gravity (see four capabilities), but the realization of its full promise relies upon a diverse array of constituent parts, many of which are likely nonnative to any specific vendor stack.

Which is why, when we evaluate these digital marketing hub vendors, we consider both native capabilities and extensibility. Why? Because, while a digital marketing hub may invite a certain gravitational attraction, it depends on the considerable energy of its satellites. Beware of hubs that purport to do it all, for the digital marketing universe is vast and even the most capable vendor is infinitely smaller by comparison.

Een organisatie die tegenwoordig tijdig op de behoefte en veranderingen in de markt wil inspelen moet Data Driven ingericht zijn. Behalve een toenemende explosieve groei aan data, neemt ook het aantal data-bronnen, diversiteit, variatie in de datastructuur en formaat sterk toe. Zet je meer mensen op de BI-afdeling om deze workload te verwerken maar blijft de verbetering van de ‘output’ significant uit? Wat is dan het knelpunt in uw BI-team?

Single Source of Truth (SSOT) is onhoudbaar
De meeste BI-tools gaan uit van een ‘Single Source of Truth’ (enkele versie van de waarheid), terwijl dit bij het huidige data aanbod zeer zeker niet het geval is. Een aanzienlijk deel van de inspanningen binnen een BI-afdeling is dan ook gericht op het schonen van de data (SSOT creëren) zodat BI-analyses en rapportages ongestoord blijven werken.

Met de sterke toename van het aantal databronnen (denk ook aan Internet of Things) wordt het steeds moeilijker om aan de SSOT voorwaarde te blijven voldoen. Ergo, terwijl de druk toeneemt om steeds sneller, accurate stuurinformatie te leveren, neemt de ‘vervuiling’ van de data-bronnen verder toe. Zo ontstaat een duivelsdilemma: Snel rapporteren met fouten of correct rapporten maar later en met dan achterhaalde gegevens. Oplossing: Meer mensen op de afdeling zetten voor data cleansing! Een korte termijn en weinig duurzame oplossing.

Verwijder de bottleneck
Onze ervaring is dat de nieuwste ontwikkelingen op het gebied van zelflerende algoritmen en robots het mogelijk maakt om data automatisch te verzamelen, te herkennen, te rubriceren en de databronnen slim elkaar te laten verrijken. Elke toevoeging van nieuwe databronnen geeft extra informatie waarmee de benadering van de waarheid steeds beter wordt. In plaats van een ‘Single Source of Truth’, wordt zo de meest waarschijnlijke benadering van de waarheid gecreëerd. Een ‘waarheid’ die met meer bronnen steeds nauwkeuriger wordt en uiteindelijk beter is dan een SSOT.

Automatisering van het proces van data cleansing scheelt veel tijd, inspanning en data correcties aan de voorkant van BI, terwijl het ook nauwkeuriger is. De BI-medewerkers kunnen hun tijd dan besteden aan het analyseren van de informatie: Data Analytics zoals het bedoeld is.

De kracht van een hele nieuwe generatie BI-tools zit ‘m duidelijk in de verwerking van data in al zijn facetten en niet in de meest fancy drill downs en presentatie mogelijkheden.

Koop geen oude wijn in nieuwe zakken!
Een Data Driven onderneming worden begint bij correcte en actuele data. Uit een inventarisatie door Gartner blijkt dat BI/Analytics in 2016 op plaats één van de CIO-prioriteitenlijst staat. Ook PENDARR eisen uit de financiële wereld maken de keuze voor een passend BI/Analytics beleid een serieuze zaak.

De requirements voor de nieuwe generatie BI-tools betreft niet alleen de informatiepresentaties, opmaak en gebruiksgemak, maar vooral de manier hoe omgegaan wordt met de aangeboden data.

Ben je als organisatie bezig met het kiezen van een BI-oplossing? Koop geen oude wijn in nieuwe zakken met modern uitziende (uiterlijk) tools die hun oorsprong en kern nog hebben in het pre Big Data tijdperk. Deze kunnen niet omgaan met ongestructureerde data uit meerdere bronnen. Zij eisen voor een goede werking nog steeds een SSOT bron met alle ‘gedoe’ rond data cleansing.

Een verkeerde keuze betekent veel extra werk, kosten en teleurstellende resultaten. Houdt u zich echter aan de volgende tien geboden –in willekeurige volgorde- dan weet u zeker dat u de belangrijkste requirements voor een weloverwogen keuze heeft ingevuld.

• Via uw BI-tool is veel organisatie-, en medewerkersgevoelige informatie beschikbaar. Het is van groot belang dat deze informatie niet in onbevoegde handen terecht komt zowel binnen als buiten uw organisatie. Op welke wijze is dit te beveiligen en wat is de kans op een datalek?
• 
  Wie gaat de tool gebruiken en is de tool voor de doelgroep gebruikersvriendelijk? Is support aanwezig en in welke vorm is deze beschikbaar?
• 
  Welke rapporteerfuncties moeten erin zitten en wat zijn nice-to-haves. Hoe lang duurt het voordat (complexe) rapporten beschikbaar zijn en in welke vorm.
• 
  Scenario rapporten: ss de BI-tool in staat om op basis van scenario’s, rapporten aan te maken.
• 
  Mutiple devices support: uw beoogde BI-tool zou niet gelimiteerd moeten zijn tot een enkel device en locatie maar locatie (geografisch) en device onafhankelijk beschikbaar moeten zijn.
• 
  Ontwikkelingen en zeker op het gebied van BI en Business Analytics gaan snel, in welke levencyclus fase staat de leverancier en zijn BI product. Kan het toekomstige ontwikkelingen volgen?
• 
  Open/gesloten architectuur. De keuze voor open of gesloten architectuur moet aansluiten op het beleid wat binnen uw organisatie is opgesteld hiervoor.
• 
  Data. Zoals betoogd moet de tool om kunnen gaan met een diversiteit aan data en ‘waarheden’.
• 
  Real-time. Wordt nieuwe beschikbare data direct verwerkt en is de informatie direct beschikbaar of niet en hoe belangrijk is dat?
• 
  Geen enkele organisatie is hetzelfde. Het vaststellen van de belangrijkste requirements voor uw organisatie is daarom maatwerk. Of u hiervoor een externe specialist voor wilt inzetten is afhankelijk van de kennis die binnen uw organisatie aanwezig is.

Source: Emerce

Over the course of last year, we saw the marketing industry monitor a number of emerging trends including wearables and facial/voice recognition, and experiment with new tools and techniques such as VR and augmented reality. 

For example, in October, we a saw a campaign from New Zealand health insurance company Sovereign that won an International ECHO Award for integrating a wide range of datasets into a campaign which drove customer signup, lead generation and sales. They integrated new data streams from activity trackers, gym networks and grocery stores to reward customers for healthy behavior. This new data also powered timely, tailored notifications across platforms. Notwithstanding the large undertaking, Sovereign was able to improve health outcomes and increase policy renewals, reversing a negative trend for the company.

In 2018, I expect that these features will evolve in ways that will help marketers better understand businesses, consumers, and competitors. Here are a few predictions for what we can expect to see this year: 

Data is a horizontal that cuts across all of marketing, yet to date many organizations (some very large organizations) are not yet data-driven. They are realizing that today’s technology and processing power enables organizations to use data informed techniques to enhance customer experience. They’re realizing that to be competitive they must pivot toward data-driven marketing techniques including data-informed design and messaging to personalize offers that resonate with individual customers based on their individual needs and interests. Look for deep-pocketed advertisers like P&G to play catchup with a vengeance in the data-driven marketing space.

Data Quality, Brand Safety, Transaction Transparency and Transaction Verification

We all know that massive amounts of data can be overwhelming. And of course, transforming data into actionable insight is the key to maximizing marketing ROI and enhancing the customer experience. Yet there is too much spurious data that is dangerous and costly. While it is a cliché, “garbage in equals garbage out” still rings true. This has been particularly evident in the digital advertising space with bad actors using bots to mimic human behavior. 

Additionally, some algorithms have gone awry in the digital ad space causing potential harm to brands by placing ads in undesirable spaces. Client-side marketers cannot tolerate fraud or waste. Consequently, the supply-side has been injured as client-side marketers began reducing their digital ad buys. Look for supply-side solution providers to increase their efforts to attack such problems utilizing tools and techniques like massive processing engines, blockchain technology, better machine learning and collective concentrations of power like trade associations that bring organizations together to collectively identify and address issues that organizations struggle to solve on their own. 

Timing and the Propensity to Buy

While algorithms may be able to predict the next site at which a potential customer will land, they haven’t yet fully incorporated the ages old data-driven marketing technique of correctly timing a compelling offer. Look for leading solution providers to utilize more machine learning and AI to better incorporate timing into their ‘propensity to buy’ calculations.

Third Party Data and the Burgeoning Duopoly 

There is a balance of power issue developing in the digital ad space as Google and Facebook continue to gain dominate market share momentum in the digital ad spend space (presently estimated at a combined 84%!). Look for “rest of the world” market forces to develop innovative solutions to ensure that competition and innovation thrives in this space. 

Responsibility 

The data and marketing industry thrives on innovation and the technological advancement that allows us to build connections with our customers based on truth, results and trust. Acting responsibly is paramount to building brand loyalty. As more hacks and breaches occur, this large problem will attract entrepreneurs seeking opportunities to solve such problems. While it is very disturbing the see large organization like Equifax fall victim to a data breach, our data and marketing industry is stocked with brilliant minds. Look for highly encrypted cloud-based security vaults to surface. And I suspect that while many organizations may feel reluctant to house their data in the cloud, look for them to realize that it is far more secure than keeping it “in house.”

Education will Evolve

While a bachelor’s degree is a critical requirement for many marketing jobs, the marketing degree hanging on the wall can’t keep marketers up to speed with the ever-increasing rate of change in our data-driven marketing industry. IoT, big data, attribution woes, and integrating online and offline touchpoints, identity across platforms, channels and devices, emerging technology and techniques are all examples of daunting challenges. 

In 2018, expect to see a surge in continuous talent-development programs, not just from academics, but from practitioners and commercial solution providers that address new challenges every day. Look for powerful video-centric platforms like DMA360, a crowdsourced platform for solution providers to bring their solutions to the market which incorporates social media techniques to curate the content through user upvotes. We all know that knowledge drives the competitive edge!

Author: Tom Benton

(chief executive officer at the Data & Marketing Association)

In today's digital marketing world, competitive intelligence often takes a back seat to all the key performance indicators (KPIs) on which marketers are focused—open rates, social engagement metrics, lead-to-sales opportunity conversion rates, etc.

That inward focus on how well you are doing with your revenue-driving marketing tactics is critical. But it can lead you to celebrate the wrong things. Don't let your KPIs overshadow the importance of knowing exactly how your digital marketing strategies are performing in relation to your peers who are competing against you in the market.

If you forget to look at the bigger picture, you'll miss a perspective that, well, separates the best marketers from the mediocre ones.

You can easily keep tabs on how your campaigns measure up against others in your industry without hiring an expensive third-party research firm. Of course, there may be times when you do need customer research and use a fancy detailed matrix of your competitors for in-depth analysis for identifying new products or for market sizing.

But I'm talking about a quick and easy dashboard that measures you, the marketer, against your competitors.

Why Spy?

Competitive intelligence helps you...

• Increase your chances of winning in the marketplace
• Shape the development of your digital marketing strategy
• Create a strategy for new product launches
• Uncover threats and opportunities
• Establish benchmarking for your analytics
  Most businesses do not have the luxury of having a dedicated employee, let alone a dedicated team, to gather and analyze gobs of data. However, you can easily track basic KPIs to inform decision-making at your company.

Having analyzed the digital marketing strategies of numerous companies of various size and in various industries, including e-commerce, SaaS, and travel companies—and their competitors—I suggest the following for benchmarking.

Website Performance Metrics

To track the performance of a website, gather data from sites such as SEMRush, Pingdom, Similarweb, and Alexa. While that data is not always accurate when you compare three or four competitors at once, you can spot trends.

Important metrics to monitor include the following:

• Website visits: The average number of visitors per month can easily size up how popular you and your competitors are.
• Bounce rate and site speed: Correlate these two metrics. That's how you can determine whether you need to make changes to your own website. For example, if your website has a high page-load time compared with your competitors, that will impact your page rankings, bounce rate, and overall customer satisfaction.
• Geographic sources of traffic: Look at what percentage of visitors comes from what regions. That's critical if your company plans to expand beyond its current geographical presence. It will also allow you to spot global opportunities by finding gaps in distribution when looking at all competitors.
• Website traffic by channel: See where your competitors choose to spend their time and money. For example, a company that has a higher percentage of visitors from email probably has a large prospect database. If you look at their website, you can examine how they collect data for their email marketing programs. Are they getting website visitors to sign up for newsletters or special offers? If not, they may be purchasing prospect data from a data provider. You can adjust your own strategy to ramp up marketing campaigns in areas where your competitors are not actively engaging prospects, or to increase spending in areas where they are outperforming you.

Benchmarking reports from industry research reports are also helpful for tracking average open, click-through, and conversion rates.

By putting together your newly found competitor insight and your own metrics, including your past performance, you can establish your own benchmarking.

Mining for More Data

Where are your competitors spending their advertising budgets? How are they using social media and PR? What jobs are they posting? Those answers are not hard to find, and they provide powerful insights.

• SEO/PPC research: Tools are available to help you determine what ads your competitors are running and how they rank for particular keywords. Check out SEMRush, SpyFu, and WhatRunsWhere. You can also look at their overall spending for PPC campaigns. Depending on the source, however, the accuracy of this data can be as low as 50%. So use it for gauging overall direction, but don't rely on it entirely.
• Social media: This is probably the hottest area of marketing and the hardest to assess. Mining data on social channels is especially tough when tracking consumer brands. It's best to monitor your competitors' activities monthly, and make sure to look at the posts ad promotions that companies generate. When updating or changing your strategy, you should have a solid understanding of what social media channels your competitors are using, types of posts they are making, how frequently they are using social media, and how successful they are (including number of users and levels of engagement).
• PR: Press releases, financial reports, and thought-leadership blog posts distributed by your competitors provide great insight into their partnerships, possible marketing spending, and other initiatives.
• Job postings: From time to time, take a look at LinkedIn or other job sites and you can get a good idea of where and how the company plans to expand.

Frequency of Competitive Analysis

The answer depends on the type of business that you have and the competitive landscape.

For example, if you are selling a product in the SaaS Cloud space where you have 10 competitors, most of which are leading innovators, it makes sense to track their every move. However, if you are a B2B company and you have only one or two competitors in the manufacturing sector, you probably can get away with doing some basic benchmarking once every quarter.

It is advisable to do a competitive analysis prior to changing strategy, launching a new product, or making tactical plans for the next quarter or year.

Don't Be Afraid: Know Where You Stand

Here's the bottom line: Don't get too excited about your 5% jump in email open rates, or passing a "likes" milestone on Facebook. Have the courage to see whether you are really a marketing rock star by benchmarking yourself against your competitors. Your business needs to know what your competition is doing. And I don't mean just knowing your competitors' products and pricing.

With the insights you'll get from these tips and tools, you will be able to create a solid strategy, spot-on tactical plans, and (at the very least) a fantastic presentation to your executives or board.

Source: MarketingProfs

How to measure the translation of online marketing performance to offline sales

Quantifying the offline impact of online marketing, and in turn, your website, is one of the important analytical challenges multi-channel businesses face. This article focuses on the multi-channel retail use case. People shop across channels, but online businesses do not commonly measure marketing return on investment this way. It’s important not to assume an incremental relationship exists between online and offline. However, discovering either way is valuable. This type of insight is often called ‘ROPO’ : Research Online, Purchase Offline. Also sometimes referred to as ‘O2S’ or Online to Store. The ROPO effect is described as a ratio. For every 1 sale online, you may create 0.5 sales offline for example. ROPO is one of the ‘big boulders’ of insight, that can be hard to move, for multiple reasons including:

• Siloed data. The inability to connect customer data from online to store, and visa-versa, is commonplace.
• Established return on investment measures and budgets are tough to change, and rightly so!
• A lack of trust in statistical methods, with a healthy skepticism against models that predict scenarios of increased digital spend, sustain inertia.

The implications of this, especially at times of economic uncertainty, are significant. Not knowing what the marginal return on investment of marketing spend beyond the channel, can lead to optimization and investment, that is stifled by a sub-optimal measurement framework.

Measurement as a competitive advantage

To give a real-world example, consider a retailer, with e-commerce and bricks-and-mortar stores. In this organization, there are many differences of opinion regarding the role of the website in multi-channel and a conventional wisdom that serves to sustain the status quo of a siloed approach to marketing measurement. Traditionally, their primary budgetary spend on digital marketing is in paid search (PPC) advertising, the results of which are measured only for conversions online. The impact of this, is such that the ROI for PPC is limited to in-channel conversions, based on a limited view of the diminishing marginal return.

Why does this matter? Risk

The risk to this business is in stifling the right thing to do for all channels, by limiting their measurement model to one channel. For businesses that have not established a multi-channel measure, there are disadvantages. They cannot spend online to levels that take into account an offline conversion value, meaning that they may lose in advertising bidding auctions against other businesses that have already proven this. Imagine the following situation:

Business A may have quantified, through various experiments and ongoing measurement, what the additional marginal return is offline for spend online. And this company adjusted their paid search optimization parameters, and ROI measures, accordingly.

Business B may not have achieved this insight, or haven't been able to prove it with enough confidence to unlock additional investment and change incumbent ROI frameworks.

In this scenario business A can profitably grow online market share, whilst benefiting their retail estate. Business B loses out, since they cannot spend beyond their long established curve of diminishing marginal return, which only takes online into account. What did ‘Business A’ do differently? What follows is a description of three techniques, that can bring an organization closer to quantifying the offline impact of their online marketing activity. We say ‘bring closer to’, because measurement is rarely perfect. It merely describes the world in a way that brings you closer to the truth. These approaches can, in combination, paint a comprehensive picture as to whether or not there is a relationship between digital spend online, online research behavior and sales in store.

Marketing Mix Modeling (MMM)

This type of study uses aggregate data and can be used to quantify the incremental impact of the inputs (e.g. search marketing spend data) to the output (e.g. store footfall or sales). To be successful with this type of modeling, it requires either specialized software or statisticians skilled enough in econometric techniques (or both), and significant volumes of time-series data. Considerations:

• Historical representative sales traffic and footfall data for online and in store are required.
• Consider time lag in the analysis, there may be an effect on the correlation of online activity to in-store.
• Consider seasonality in the analysis, seasonal and promotional peaks will need to be controlled for.
• Articulating the output of such models is important. Influencing skeptical stakeholders will require them to be brought along the journey and have their voice heard.

Known customer tracking (using email as the conduit)

Known customer tracking, in this example, uses the customer’s unique ID which resides in the CRM system. This is populated in email links and captured in web analytics, then tracked through to sales in all channels. It is possible to leverage the insights from known customers, via your CRM system. Assuming that a business has a single customer view ID residing in the CRM system, the ID can be populated in the email links as a parameter. This parameter can be collected by the website analytics to start tracking ‘known visitors’. It is then possible to reconcile, from known visitors (researchers) online, to sales (purchases) offline, by joining the web analytics and offline sales data together. This gives the raw materials to quantify: from X researchers online, there are Y sales online and Z sales offline. Therefore for every sale online, we achieve Z sales offline (Z can of course be a fractional amount).

One challenge with this technique is whether or not the business believes that email activity has a particular bias toward offline vs online. Therefore, this insight should be used to underpin one or more different measurement techniques rather than be relied on in isolation to provide the insight upon which investment decisions are made.

Holdout tests

Holdout tests are a great way to take advantage of advertising technology that can geo-target campaigns, such as paid search, enabling marketers to identify like for like regions. Marketers can then up-weight or down-weight spend, tracking results across online and retail. A business with a large enough retail presence, can split up the country into like for like city regions, for the purpose of conducting an A/B group test. For the A group, spend could remain at a baseline, and for the B group spend could be up-weighted. This requires the orchestration of the geo-targeted advertising campaigns, budget, online spend, conversion data, offline sales and footfall data. The resulting online traffic and sales, store footfall and sales are compared statistically for each of the regional groups, A vs B. The output of this analysis can reveal whether there is a statistical relationship between the digital spend and retail footfall and sales. Of course, costs need to be considered. Missed opportunity in the case of down-weighted regional spending, or increased budget for up-weighted regions, depending on the design of the test. Therefore adequate skills, technology and methodology are paramount. The value of insights delivered is high, but so are the risks of delivering ambiguous results. This makes this technique a worthwhile endeavor that should be approached with due care.

Challenge the measurement status-quo

There are other techniques in the marketing tool box, such as click to call and in-store beacons for example. Developing this level of understanding is not a one and done activity. Invest the time and effort to learn the insights that are valuable and elusive, because in doing so, you can gain a competitive advantage. Lastly, don’t stop with one experiment, if you can come to similar conclusions using different techniques, the confidence level of those you have to convince, should increase. By conducting three types of measurement and triangulating the results, you can create a solid foundation upon which to make decisions on how to update your marketing investment, efficiency metrics and ROI measures.

Source: Gartner

CMOs will drive marketing technology spending to $32.3B by 2018, reaching a compound annual growth rate (CAGR) of 12.4%. From 2014 to 2018, marketing technology spending will reach $130B for the 5 year period.

These and other insights are from IDC’s recent webinar The Marketing Software Revolution: Strategies for Buyers and Sellers, presented by Mary Wardley, Vice President, Enterprise Applications and CRM and Gerry Murray, Research Manager, CMO Advisory Service .

IDC is seeing CMOs influence spending in areas outside the traditional definition of CRM, and has created the 2015 Marketing Technology Map to track these new categories. The additional areas of marketing spending IDC is including in their forecast taxonomy are content, data and analytics, and managementand administration. One of the most valuable insights gained from this webinar was seeing how IDC is seeing CMOs redefine the direction of marketing spending based on client inquiry calls and their analysis of the CRM market.
The following are the key take-aways from the webinar:

· IDC forecasts spending on CRM applications will reach $31.7B in 2018, attaining a CAGR of 6.9%. The following graphic illustrates forecast spending by contact center, customer service, marketing automation and sales automation

IDC’s 2015 Marketing Technology Map is designed to capture CMOs’ total impact on marketing technology spending. The green area of the 2015 Marketing Technology Map titled Interaction is what represents traditional CRM functionality today. IDC’s inclusion of content, data and analytics and management and administration reflects how the role of the Chief Marketing Technologist continues to accelerate in all businesses.

Marketing technology spending will increase from $20.2 billion in 2014 to $32.4 billion in 2018 based on the the 2015 Marketing Technology Map.The following graphic provides forecasts for interaction systems (traditional CRM), Content, Data and Analytics and Management and Administration.

90% of the growth in the IT industry will come from cloud-based solutions. Cloud platforms, creative services and IT services are emerging as a combined catalyst enabling Marketing-as-a-Service (MaaS), which IDC is seeing growing rapidly from a client planning and spending perspective.

IDC

Staand voor het Retail schap maakt de consument in recordtempo een veelheid aan afwegingen. Krijg ik waar voor mijn geld? Hoe is de prijs? Wat koop ik echt? Is het gezond? Hoe weet ik dat het ene product gezonder is dan het andere? Een complex samenspel van afwegingen dat leidt tot het wel óf niet plaatsen van het product in het winkelmandje. Dit fenomeen doet zich niet alleen voor in de supermarkt maar ook bij klanten in allerlei andere (online) verkoop omgevingen.

Leveranciers ‘helpen’ de consument door op de verpakking te vertellen wat er in zit: bijvoorbeeld ‘vol met gezonde plantsterolen’ of ‘verlaagt de bloeddruk’. De klassieker ‘goed voor hart en bloedvaten’ is misschien wel de bekendste voedingsclaim aller tijden. 

De klant lijkt met deze informatie geholpen. Lijkt! Want is dit ook echt zo? Natuurlijk, in eerste instantie wel. Maar als zij even langer doordenkt roept de marketing claim natuurlijk nieuwe vragen op (zoals informatie altijd leidt tot nieuwe vragen: dat is hèt kenmerk van informatieprocessen). Nieuwe vragen zijn: Hoe gezond zijn die sterolen nu eigenlijk? Hoeveel zitten er in de alternatieve producten die er niet over reppen? Wat doet een plantsterool voor mij? 

Conclusie: Product gerelateerde informatieverstrekking via claims is al snel aan erosie onderhevig bij een steeds slimmer wordende consument. Dat betekent dat naarmate de tijd voortschrijdt steeds meer of specifiekere informatie moet worden toegevoegd. Daarmee worden data en informatie een intrinsiek onderdeel van het product!

Deze ontwikkeling is natuurlijk prima voor de consument maar stelt nieuwe eisen aan de product manager en marketeer. Deze moet zorgen voor steeds specifiekere en valide productinformatie die aangeeft hoe het product zich onderscheidt van andere producten.

Dit betekent dat de product manager de concurrentie zo goed moet kennen dat hij of zij op eigenschap- of ingrediënt niveau kan vertellen hoe het product zich onderscheidt van andere producten. Alleen dan kunnen slimme en valide claims worden gekozen en zo helder mogelijk aan de klant worden gecommuniceerd.

In een markt die steeds kennisintensiever wordt, speelt competitive intelligence (CI) een steeds belangrijkere rol in product management en marketing communicatie. Operationele CI is effectief toe te passen in drie stappen.

1. Data gedreven ontleden van concurrerende producten

Het maken van slimme claims vereist dataverzameling over concurrerende producten. Langs voor de doelgroep relevante dimensies moeten concurrerende producten worden geïdentificeerd en in kaart worden gebracht om tot een adequate productvergelijking te komen. 

Databeschikbaarheid maakt het inventariseren van producteigenschappen meer of minder makkelijk. Dit verschilt per product. Van levensmiddelen is vaak data beschikbaar via productdeclaraties die op de verpakking te vinden zijn. Daarnaast zijn er (vaak dure) databases waarin deze producten zijn terug te vinden. Niet voor ieder product zijn de eigenschappen eenvoudig te achterhalen. Soms zijn daar creatieve datacollectie methoden voor nodig. 

2. Analyse van producteigenschappen op relevante dimensies

Om tot zinvolle inzichten te komen moet de verzamelde data worden geïnterpreteerd langs voor de doelgroep relevante dimensies. In het voorbeeld van het levensmiddel kunnen deze dimensies bijvoorbeeld zijn ‘voorzien in energiebehoefte’, ‘mate van verzadiging’, ‘bijdrage aan spieropbouw’, ‘calorie rijkheid’, etc., etc. 

Producten kunnen goed of minder goed op deze dimensies scoren. Voor diverse claims is het van belang te begrijpen hoe deze assen zich tot elkaar verhouden. Als een product claimt bij te dragen aan gewichtsvermindering is de as ‘rijkheid aan calorieën’ maar ook ‘mate van verzadiging’ van belang. De aanwezigheid van een bepaald ingrediënt kan op de ene as een hoge score opleveren terwijl het juist op de andere as tot een lagere score leidt. Om tot een valide claim te komen niet onbelangrijke informatie! Een sprekend voorbeeld is het ‘light’ product wat in zichzelf misschien wel ‘light’ is, maar tot weinig verzadiging leidt waardoor men daarna weer snel andere producten tot zich gaat nemen. Een voor de doelgroep relevante interpretatie van de verzamelde data staat in deze stap van operationele CI centraal. 

3. Inzichten concreet maken door mogelijke acties te benoemen

Tenslotte is de proof of de pudding natuurlijk in de eating. Welke claim kan legitiem en valide gemaakt worden? De met CI geproduceerde inzichten leveren in deze fase niet de formulering van de winnende claim op. De inzichten vertellen wel welke claims valide kunnen worden gemaakt, op welke scores de claims zijn gebaseerd en hoe het product zich qua scores verhoudt ten opzichte van de concurrerende producten. Behalve competitief inzicht en input voor marketing levert deze fase van de aanpak ook onderzoeksvragen op voor productontwikkeling en research. De productmanager of marketeer die een met CI opgebouwde kennisvoorsprong weet te behouden is in een kennisintensieve samenleving spekkoper.

Auteur: Egbert Philips

Bron: http://www.hammer-intel.com/nl/portfolio/

Market intelligence neemt een vlucht. Nu ondernemingen hun interne informatiehuishouding in toenemend mate in orde hebben

gaat de aandacht (opnieuw?) uit naar de informatievoorziening met betrekking tot de markt van ondernemingen. Opnieuw? Ja, opnieuw!

Als sinds de ’60er jaren staat het onderwerp midden in de belangstelling maar onder invloed van informatietechnologische ontwikkelingen werd het steeds naar de achtergrond gedrongen door aandacht voor de interne optimalisering van de informatiehuishouding. Executive informatiesystemen (een term uit de jaren ’80) leidde tot BI en BI tot DWH, ETL, Reporting en score carding. De toename van data op social media, het net en de mogelijkheden op het gebied van ongestructureerde data – data mining maar ook machine learning voedden nu opnieuw de aandacht voor toepassing van technologie bij het beter kennen van de bedrijfsomgeving. Het belang daarvan is dus niet veranderd maar de mogelijkheden nemen wel toe.

Drie jaar geleden werd Hammer, market intelligence opgericht met als doel bedrijven van market intel te voorzien met gebruikmaking van moderne data technologie. Egbert Philips (Director van het in Arnhem gevestigde Hammer); “Wat betreft management informatie zou er minstens zo veel aandacht moeten zijn voor het kennen en doorgronden van markt en bedrijfsomgeving als voor de interne prestaties. Dit zou niet afhankelijk moeten zijn van technologische mogelijkheden. De ontwikkeling van data science en big data technologieën maken het wel mogelijk market intelligence beter en efficiënter in te richten. Daar richten we ons met Hammer op. We willen een partner zijn voor bedrijven die hun markten structureel willen kennen en doorgronden. Informatie technologie blijft daarbij een middel maar wel een heel belangrijk middel.”

Hammer is weliswaar een jonge onderneming maar bepaald niet nieuw in het veld. De oprichters zijn reeds jarenlang actief in market intel en de toepassing daarvan in onder ander strategische planning vraagstukken. Hammer ondersteunt echter ook meer tactische beslissingen. Vraagstukken met betrekking tot pricing, sourcing/inkoop, het kiezen van distributiepartners, productontwikkeling en business development kunnen niet goed worden beantwoord zonder input van marktinformatie.

Eind november organiseert Hammer een klantevent. Wanneer u geïnteresseerd bent stuur dan een e-mail naar info@hammer-intel.com

http://www.hammer-intel.com

The impact of analytics on the field of marketing

The rise of analytics is affecting every industry. The field of marketing is ahead of the curve, having been a metrics-driven industry for decades, but which metrics a company decides to focus on, how they track, report, and analyze those metrics, and what they do with that analysis makes a big difference. CEO Garrett Mehrguth from Directive Consulting talks about the impact that analytics (overall and customer-facing) have had, have, and will have on the marketing world.

Beware analysis paralysis

If you’re in a data-driven industry, then there’s no downside to tracking and analyzing your performance data. However, this cuts both ways: the idea of “if it’s not measurable, it’s not valuable” has taken hold in a lot of marketing organizations. Relatedly, sometimes organizations will latch onto a metric just because they can measure it, regardless of whether it is truly tied to results. To complicate matters further, having too much data can cause organizations to become so fixated on tracking every metric that they spend less time actually doing their jobs. People get lost in dashboards, fiddling with numbers instead of actually making progress. These companies get stuck in a morass of data points, charts, and dashboards that look and feel important, but might not help improve the bottom line. This type of dashboard fetishism that stymies action is an example of analysis paralysis.

“I see this constantly happening to in-house marketers and others. You get so much data you’re inundated with and you want to track everything, and then you forget that keeping track of everything, even when it’s automated, becomes such a component of your time that you actually no longer have time to move the needle. You’re spending all this time in this analysis paralysis…” said Garrett Mehrguth.

Having the right focus

In a world of distractions, both companies and individuals are constantly exhorted to have the right focus (while being exposed to a slew of inspirational posts, articles, Instagram accounts, etc). What this means for marketing companies (or any company with involved in analytics), is that they should move away from vanity metrics and focus on the KPIs that really make a difference in their business or their clients’ businesses.

Embedded analytics solutions give end-users easier insights into their own metrics by eaasily combining complex data from multiple sources. Buying that solution instead of building it in-house allows companies to build and ship robust analytics to their customers without investing a ton of developer resources in something that’s not the core competency of their business. However, where marketing companies can truly add value to their clients’ lives is with expertise: understanding which metrics matter to their bottom line and what those numbers and trends mean is important for the kinds of relationships that marketing companies should be trying to build with their clients.

“We don’t work with any organizations that don’t have access to their own analytics and have a pretty good idea of what’s going on.” said Garrett Mehrguth. He also stressed that knowing which metrics matter most and having analytics that let them see and act on those numbers leads to better outcomes for marketers especially: “Knee-jerk marketing is the worst marketing in the world, and a lot of that reactivity comes from what marketers think they’re marketing should be accomplishing, not what reality says that their marketing can accomplish.”

The right analytics solution gives clients a detailed look at how their companies are performing on their own terms and compared to their market peers. If a company is down year-over-year and their entire segment is down, then this level of transparency helps them see that and adjust expectations accordingly. Meanwhile, if their growth has been sluggish, but they’re still beating competitors, then they can see that as well. It’s all about helping users to get a better understanding of their world and keep their mindset focused on the possible and the achievable, instead of torturing themselves with unattainable goals. This kind of transparency also helps client relationships:

“The reason I love being transparent and being held accountable to the quality of our efforts and our recommendations is that if you make an account more than they’re paying you, it’s pretty hard to get fired.” althus Garrett Mehrguth.

The holistic approach

So often, when working with a consulting firm, the client is focused on end results, but doesn’t have any idea whether or not the relationship is working well until it’s either too late or the contract is over, at which point they may or may not have gotten what they wanted out of it. In-depth analytics allow service-providers to prove efficacy and value quickly, easily, and continuously. One interesting thing that Directive does with their in-house analytics takes their relationship-building to the next level. Their account managers use in-house metrics to take a holistic approach to customer service:

Garrett Mehrguth: “We’re using our analytics for quality control based onqualitativedata, all based on client feedback: ‘hey, this client’s a little uneasy,’ ‘hey, this client’s really happy,’ ‘this client needs some more attention.’ And now what we’re doing is using that data across the entire portfolio to get what we call leading indicators.”

These leading indicators, created using a mix of the complex data at Directive’s disposal for in-house purposes (not client-facing), help them tie the actions the team is taking with clients to the results those clients are experiencing. In some cases, this means adjusting expectations or allocating additional resources to correct a situation. What it helps prevent is unhappy customers complaining late in the process, as per Garrett Mehrguth:

“Sometimes it takes a little while to right the ship of a struggling client, but if you don’t know about that and you’re just waiting until they complain—which they have every right to do, because you haven’t been doing your job—then you’re behind the eight-ball.”

So when it comes to marketing, in-depth analytics are good for marketers, marketing clients, and marketing service companies and consultants. They’re so important that Garrett Mehrguth sees major hurdles in the future for any marketing company that doesn’t offer detailed reporting and support to help their clients get the most out of it:

“If you’re in marketing and you’re not correlating your efforts back to actual revenue with analytics, you’re going to struggle to close clients.”

Conclusion

Analytics are everywhere. From a start as spreadsheets and CSV files to the era of self-service and the looming AI revolution around us, no industry can afford to stand still when it comes to its analytics. Marketing, steeped as it is in a history of metrics and data, is a leading-edge case. Marketers have more data than ever before and are struggling to avoid analysis paralysis and have the right focus. Service providers have to do more than just deliver amazing analytics and insights: they also need to be supportive, helping to guide their clients to make the smartest decisions and understand their markets. If your business can manage this, itll be able to prove value, delight its customers, and build the future in your desired way.

Source: Sisense