Great case study from Think with Google and Anheuser-Busch InBev on total #videoadvertising measurement, bridging Linear and Digital advrtiding- https://bit.ly/3ywj3XN
Love the three axioms laid out- #1 get out of channel/platform silos, #2 plan for total reach, #3 Balance long-term on short-term. For #2 beyond Google Reach Planner mentioned in the article, it is important to connect linear and Digital audiences using #ACR data mapped to device IDs/mobile Ad IDs (MAIDs). For #3, long-term impact can easily be added by leveraging YouTube's BrandLift tool (https://lnkd.in/ezAWF85A). In fact a cool add to this approach would be to test audiences built from TV in Digital to measure the combined lift of TV+Digital on awareness.Do you need a vacation out of office email strategy?
Have you ever returned from vacation, where you were able to disconnect, recharge and rejuvenate, only to come back to a mountain of email that immediately elevated your stress to pre-vacation level? Summer is in full swing and most people are emerging from lockdown and planning some sort of time-off. And coming back from any meaningful amount of leave means you need to have a strategy to deal with email, especially since the advent of the pandemic brought a 50% increase in email volume. Here is is a great read on the topic. Some great advice in this quick read. Interesting observation by the author that the the vast majority messages she received during her vacation didn't warrant direct response from her. Should we exclude people that have OOO messages on that indicate more than 2-3 days, unless they are critical to the conversation? Or may be if critical write them a separate note with delivery delayed to the day of their return? I don't know, but in any case, this is an area where I suspect corporate culture will evolve soon, because it is evident it is a stress inducer! #email #strategy #corporateculture #worklifebalance #vacationmode
Too much stimulus in the economy?
The Conference Board forecasted a record US Real GDP growth of 9.0 percent (annualized rate) in Q2 2021 and 6.6 percent (year-over-year) in 2021. Compare that to 2019 real GDP growth of 2.3 percent in 2019 and 2.9 percent in 2018. In 2020, the U.S. economy shrank by the largest amount in 74 years, as unemployment rate peaked at a historic high of 14.8% in April 2020 (as of June ’21 unemployment is down to 5.9%).
University of Michigan Consumer sentiment has edged up to 85 from the pandemic low of 71.8 last April (still not quite back to the pre-pandemic high of 99.3 in Dec 2019).
This strength seems to be translating well to consumer spending. Personal Consumption Expenditures (PCE), after dropping 18% from Feb ’20 to April ’20, grew back ~28% (April ’20 to May ’21), erasing all of the declines to bring it back in line with its multiyear 3.5% annualized growth rate. The National Retail Federation revised its retail sales growth expectation to 10.5 - 13.5 percent (vs. 2020), to a range between $4.44 trillion and $4.56 trillion (up from 6.5 percent - 8.2 % expectation just 6 months back). US demand for goods and services is driving global economic recovery for the first time since 2005 (https://lnkd.in/e2KgbAX).
Of course, the sheer breadth and magnitude of the stimulus aid has directly impacted the strength of the GDP rebound in 2021. According to the Committee for a Responsible Federal Budget (https://lnkd.in/erkXHc6), of the $5.9 trillion ($5.2 trillion net) of enacted COVID relief, $3.6 trillion was committed or disbursed over the one-year period beginning last April, resulting in a nominal disposable personal income (DPI) growth of 10.6 percent, or 2X the income growth of 5% per year over the prior three years. According to CRFB, absent COVID relief and its economic effects, personal income would have fallen by about 5 percent. For now, we can be content with a turbocharged US economy (and contend with the inflation risk!). #economy #growth #retailsector #markets #inflation #consumerspending #consumersentiment
Google's not extending FLoC origin trials as part of its Privacy Sandbox Cookieless future
-33,872 browsing interest based Cohorts (FLoCIDs)
-2000 minimum number of qualifying Chrome users in a cohort
-735 minimum number sets of visited domains in a cohort. Content creator CafeMedia's AdThrive did an interesting analysis below on grouping the 34K FloCIDs into 34 sets of 1000 each (they call it KFLoCs) and mapped their top 10 content keywords. On the downside, this analysis shows fuzzy targetable interest patterns at best (foodie, outdoors, travel from a quick glance). Probably part of the reason Google apparently is not extending the trial, but instead are "hard at work on improving FLoC to incorporate the feedback we’ve heard from the community before advancing to further ecosystem testing". IMO, this doesn't mean advertisers should lift their foot off the #cookieless pedal, it is inevitable, given other major browsers have already done this. Personally, I think, if anything, the FLoC experiment highlights the need to hedge your bets with other approaches including building a #firstpartydata ecosystem and/or explore audience #identity consortiums. (https://lnkd.in/eQ3pGx7) #google #thirdpartycookies #audiencetargeting #addressability #cookieless
WFH email explosion- time to retire your inbox?
At an average minute per email (those that need a response needing more, others less), that meant 2 hours per day working through emails. With pandemic WFH, that has gone up by 50%. So you have to set aside up to 3 hours per day to deal with email. And you have to come up with strategies to block off this time especially If you have back to back meeting days. So I am all for simpler communications (and rules around email lengths- no more 3 page essays!). But project chat boards do need better organizing- love the ability to call out a specific person using @, but I should be able to filter by team member or topic.
New Product Marketing Playbook (in other words, they won’t come just because you built it)
3 under-appreciated trends in consumer behavior (and resultant imperatives for marketers)
Mike Walsh on building businesses for the 21st century @ IRI CPG Summit, Orlando-FL...
IRI CPG Blog Post: Surf’s up! Time to Ride the Online Video Wave?
The post highlights 3 reasons to get in on Online Videos today:
- Efficiently enhance your message reach on traditional TV
- Test your TV campaigns
- Reap early adopter benefits
Employee Strategy: (in?) Flexible Work Program @ Yahoo!
SetFocus: Revisiting your 2013 Marketing Playbook
On the positive side, there’s some indication including forecasts from The World Bank Commodity Price Forecast, of lower commodity prices in 2013, which can provide some tailwinds[1]. The DOE also predicts lower gas prices in 2013[2], which generally helps consumption by freeing up disposable income and driving shopping trips up.
The Employment report in February (for January) came in a bit below expectations at +157K, which is lower than the previous revised number of +196K- 2012 average growth was 181K/month.
What does this mean for your 2013 Marketing Strategy?
If economic uncertainty continues building up into mid-2013, then marketing strategy early in the year should emphasize your value proposition, focusing on share growth through Trade and Consumer promotion investment. Any relief in costs from favorable commodity pricing changes should be passed through 100% to consumers. Advertising focus, both online and off-line, should be on lower funnel that aims to increase conversions by “nudging” consumers sitting on the fence on your brands and retaining existing consumers that may be vulnerable to competitive promotional incursions. Paid Search is especially a good way to get in front of consumers one step before the purchase decision. Paid Search importance is going to be even greater in driving conversion with Product Listing Ads (Google Shopping’s new rich ads functionality[3]).
Hurricane Sandy and Income Inequality debates..
While I appreciate the point he is making, I am not sure the analysis is entirely fair. First of all the fact that everyone, irrespective of being rich and poor should have been able to retreat to safety. I view the fact that service folks continued servicing as a failure of the City authorities to enforce safety measures- businesses had no business (no pun intended) keeping employees back beyond a certain point.
That said, the income disparity between the top vs. the bottom quintile shouldn't be surprising based on economic behavior. The top 20%'s earnings being high is an artefact of NYC's ability to attract highly skilled labor that commands a wage premium, which in turn creates an abnormal demand for a secondary market of relatively lower skilled labor (nannies, waiters etc). Urbanization is known to create income inequalities for this reason- cities tend to attract from cheaper labor markets (immigrant, students etc). This is partially related to the Kuznets curve effect:
Except that the inequality continues to rise exponentially due to a free inflow of unskilled labor that is willing to compete on price with existing unskilled labor. Comparing top-bottom quintile income disparity in a city that is only ~400 Sq miles yet boasts 1.2 Trillion dollars in GDP is pointless- there is an extreme division of labor and a continuous supply of labor (skilled and unskilled) that is more than willing to compete on price. Profits/income are inversely correlated to competitive intensity, labor markets are regulated in order to contain this profit-maximizing behavior within rational limits. Now what is worrysome is that based on New York State's minimum wage and a 40-Hour work-week, the lowest wages should be ~$15,000 p.a, the fact that it averages $9,681 in the bottom quintile could indicate a significant number of the labor market working below minimum wages, which probably reflects a failure in enforcing minimum wage discipline.
Is your Vision damaging your business?
Brands aren’t built overnight and sustainable brands need an evolving strategy that will navigate economic cycles that are a lot longer than 2 or 3 years, in fact typical economic cycles are 7+ years.
What you are missing out on is an opportunity to understand how your customers are adjusting their consumption behavior as the economy waxes and wanes. Granularity of information flooding researchers in recent years has motivated business strategy to be focused on maximizing short term profits and opportunities. Don’t get me wrong, short-term planning is important- the short-term is the bridge to the long-term and public companies are answerable to shareholders in the short-term. At the same time the most sustainable brands and businesses are the ones that have the information and experience to help them adjust to economic changes. In that respect, Businesses need to be like Neural Networks- learn and adapt based on past experiences, while adjusting to newer paradigm shifts. While lifestyles evolve and change much more rapidly today than they did 10 years back, there are some consistencies that business managers need to take into account especially if they are in the B2C domain.
For example how people adjust to economic upheavals, what spending categories do they curtail during a downturn and which ones do they prioritize coming out of a downturn. If you compare the growth in Retail spend data by segments from the U.S. Census Bureau from 2004 to the spending from 2011 (2 years post the respective recessions), you will notice some remarkable consistencies. The top 3 segments by growth vs. prior year in both cases were Building Materials, General Merchandise and Restaurants, while Electronics, Apparel and Sporting/Music stores were bottom segments.
How cool would it be if you could predict how your customers are going to change their consumption preferences in a sluggish economy and an expanding economy, what trade-offs in terms of share of wallet would they make as the size of their wallet shrinks or expands? And how cool it would be if you were able to anticipate these changes in consumption preferences and adjust your product portfolio, assortment and marketing/pricing strategies accordingly? So one would think it is easy for businesses to compare what their customers did in the Great Recession vs. the 2001 Recession, but you would be surprised even with big data how few companies have less than 5 years of data readily accessible for analysis. However different we are today compared to 10 years back, some elements of history do tend to repeat and if you chose not to learn from history you may well be condemned to repeat it.